<h3>Agentic AI is emerging as one of the most significant technological shifts in modern banking. By combining reasoning, planning, and autonomous execution, it enables financial institutions to improve decision-making, streamline operations, strengthen risk management, and unlock new opportunities for sustainable growth.</h3><h2>1. From AI assistance to autonomous decision-making</h2>Agentic AI represents more than the next generation of artificial intelligence, it marks a fundamental shift in how financial institutions operate and make decisions.Unlike traditional AI, which relies on predefined rules, or Generative AI, which primarily responds to user prompts, Agentic AI consists of autonomous systems capable of planning, reasoning, using external tools, and executing multi-step actions to achieve user-defined objectives with minimal human intervention.This distinction is particularly important in banking. As financial markets become increasingly dynamic and customer expectations continue to evolve, decision-making can no longer rely solely on historical data or static business rules. Agentic AI enables banks to process structured and unstructured information simultaneously, adapt to changing market conditions, personalize financial services, and support real-time decision-making at scale.<h2>2. Building blocks and operating architecture of Agentic AI</h2>An Agentic AI system is not a single model but an integrated ecosystem composed of five core components that work together to enable autonomous decision-making.<ul><li>Instructions:&nbsp;define the agent's objectives, responsibilities, operational boundaries, and regulatory constraints.</li><li>Tools: allow the agent to interact with external systems, including financial data platforms such as Bloomberg and FactSet, execute Python code, or connect directly with Order Management Systems (OMS).</li><li>Information retrieval: combines Retrieval-Augmented Generation (RAG) with web search capabilities, enabling agents to access both internal knowledge bases and the latest market intelligence.</li><li>Memory: enables the agent to retain both short-term conversational context and long-term organizational knowledge through vector databases, allowing decisions to become increasingly context-aware over time.</li><li>Guardrails: ensure that every recommendation or action complies with internal policies and regulatory requirements. For example, an agent can automatically block investment recommendations or transactions that exceed predefined portfolio risk limits.</li></ul>Depending on business objectives, these components can be organized into several workflow patterns.<ul><li>Prompt chaining executes sequential tasks, making it suitable for processes such as preparing credit assessment reports.</li><li>Routing directs requests to specialized agents based on their domain, such as equity research, credit analysis, or macroeconomic forecasting.</li><li>Parallelization&nbsp;allows multiple analytical tasks to run simultaneously, significantly reducing processing time for large-scale portfolio analysis.</li><li>Orchestrator-worker architectures divide complex objectives into specialized subtasks managed by dedicated AI agents.</li><li>Evaluator-Optimizer workflows introduce an additional validation layer, where one AI generates a solution while another independently reviews and refines the output before execution.</li></ul><h2>3. Applications in Financial decision making</h2>As Agentic AI matures, financial institutions are beginning to move beyond task automation toward autonomous financial decision support across several critical functions.<h3>Risk profiling and credit assessment</h3>Rather than relying exclusively on traditional scorecards, Agentic AI continuously analyzes behavioral signals and transaction data to produce dynamic credit risk profiles.This adaptive approach enables financial institutions to improve lending accuracy while reducing non-performing loans, with several studies reporting reductions of up to 12%.<h3>Predictive loan underwriting</h3>Instead of applying rigid approval thresholds, Agentic AI evaluates transaction histories, electronic documentation, and behavioral patterns to predict repayment capacity more accurately.This allows banks to dynamically optimize loan approvals, pricing strategies, and credit limits while balancing profitability and risk exposure.<h3>Intelligent treasury management</h3>Agentic AI can continuously monitor liquidity across multiple accounts, automatically initiate fund transfers, recommend reinvestment opportunities, and respond to changing cash flow conditions within milliseconds.Such capabilities significantly improve liquidity optimization while reducing operational overhead.<h3>Personalized portfolio construction</h3>By combining ESG screening, macroeconomic analysis, and client-specific investment objectives, Agentic AI enables wealth managers to build highly customized Separately Managed Accounts (SMAs) for high-net-worth clients at a scale that would be difficult to achieve manually.<h2>4. Challenges of implementing Agentic AI</h2>Despite its significant potential, Agentic AI also introduces new governance challenges that financial institutions must address carefully.One of the most notable observations is the emerging AI paradox. Although nearly 80% of financial institutions across Asia report adopting AI, a similar proportion of organizations globally acknowledge that these initiatives have yet to generate meaningful bottom-line impact.Several factors contribute to this gap.<ul><li>Goal misalignment: Autonomous agents may optimize for financial performance while inadvertently violating customer risk preferences or organizational objectives.</li><li>Regulatory compliance: Financial AI systems must comply with increasingly stringent regulations, including the EU AI Act and local data privacy requirements established by financial regulators.</li><li>Pilot Purgatory: Many AI initiatives remain confined to isolated pilot projects due to fragmented organizational structures and limited cross-functional collaboration.</li></ul>To overcome these challenges, financial institutions are increasingly adopting Compliance by Design, establishing centralized AI governance frameworks, maintaining enterprise-wide AI registries, and ensuring Human-in-the-Loop (HITL) oversight for high-impact decisions.<h2>5. The Roadmap for Vietnamese banks</h2>Within Vietnam's banking sector, AI adoption remains largely focused on customer service chatbots and basic fraud detection. However, several institutions have already demonstrated meaningful progress.For example, Techcombank has applied AI to its credit assessment process, reducing loan approval time from three days to approximately six hours while improving operational productivity by around 15%. Importantly, human experts continue to perform the final review before approvals are issued, reflecting a balanced approach between automation and governance.To unlock the full potential of Agentic AI, Vietnamese banks can consider a three-stage adoption roadmap:<ul><li>Stage 1: Upgrade traditional chatbots into self-learning virtual assistants capable of continuously collecting customer behavioral data.</li><li>Stage 2: Expand AI into predictive credit scoring, intelligent fraud detection, and risk analytics.</li><li>Stage 3: Deploy Agentic AI across complex banking operations, including fully automated eKYC, intelligent investment advisory, and autonomous portfolio management.</li></ul>A key challenge remains the fragmented nature of financial data. Advancing toward an&nbsp;Open Banking ecosystem where banks securely integrate data from telecommunications providers, e-commerce platforms, and other trusted third parties will provide Agentic AI with richer contextual information and significantly improve prediction accuracy.<h2>6. VMO's Perspective: Turning Agentic AI into Enterprise Value</h2>At VMO, Agentic AI is viewed not as a replacement for human expertise, but as an intelligent execution layer that enables financial institutions to make faster, more informed, and more consistent decisions.Successful adoption begins with clearly identifying business processes where autonomous reasoning creates measurable value, followed by designing AI architectures that seamlessly integrate with existing banking systems while maintaining robust governance, security, and regulatory compliance.With extensive experience delivering AI solutions across the financial services sector, VMO supports banks and financial institutions throughout the entire AI transformation journey from strategy and solution architecture to deployment and continuous optimization. Rather than treating AI as an isolated technology initiative, VMO focuses on embedding AI into core business processes where it can create tangible operational value.Ultimately, the objective is not simply to automate banking operations, but to build trusted AI systems that enhance decision quality, operational efficiency, and customer experience simultaneously.<h2>7. Conclusion</h2>Agentic AI represents a significant evolution in enterprise AI from systems that generate information to systems capable of planning, reasoning, and acting autonomously.However, technology alone will not determine success. To translate AI investment into measurable business value, banks must establish executive-level commitment, strengthen collaboration across business, technology, and risk functions, modernize data infrastructure, and continuously develop an AI-ready workforce.The banks that lead the next decade will not necessarily be those deploying the largest AI models, but those that design the strongest operating model where autonomous AI and human expertise work together to make better financial decisions.

Agentic AI in Banking: Next Frontier of Intelligent Ops

agentic-ai-in-banking-next-frontier-of-intelligent-ops

The way healthcare professionals learn is changing rapidly. Across the Asia-Pacific (APAC) region, medical schools, hospitals, and healthcare organizations are increasingly turning to AI and AR to modernize medical education.Traditional medical training, while foundational, often faces limitations in scalability, accessibility, and hands-on practice opportunities. AI and AR technologies are helping bridge these gaps by creating immersive, personalized, and data-driven learning experiences that better prepare clinicians for real-world practice.As healthcare systems across APAC continue to digitize, AI and AR-powered education is emerging as a strategic investment for institutions seeking to develop a future-ready workforce.<h2>Why Medical Education Needs Transformation</h2>Medical knowledge is expanding at an unprecedented pace. New treatments, technologies, and clinical guidelines are continuously introduced, requiring healthcare professionals to engage in lifelong learning.At the same time, healthcare organizations face several challenges:<ul><li>Limited access to clinical training opportunities.</li><li>Growing shortages of healthcare professionals.</li><li>Variations in training quality across regions.</li><li>Increasing complexity of procedures and technologies.</li><li>Rising demand for remote and flexible learning models.</li></ul>Conventional classroom-based approaches alone are no longer sufficient. Digital learning technologies are enabling institutions to provide more standardized, scalable, and engaging educational experiences.<h2>The Rise of AI in Medical Education</h2>AI is transforming medical education by making learning more adaptive, personalized, and efficient.<h3>Personalized Learning Pathways</h3>Every learner progresses differently. AI-powered learning platforms can analyze individual performance, identify knowledge gaps, and automatically tailor educational content to each student's needs.<h3>Intelligent Assessment and Feedback</h3>Traditional assessments often provide delayed feedback. AI systems can evaluate learner performance in real time and deliver immediate insights.Examples include:<ul><li>Automated scoring of clinical simulations.</li><li>AI-based assessment of procedural skills.</li><li>Speech and communication analysis during patient interactions.</li><li>Objective evaluation of surgical techniques.</li></ul>Instant feedback allows learners to continuously refine their skills and accelerate competency development.<h3>Virtual Patients and Clinical Decision Support</h3>AI-powered virtual patients simulate realistic clinical scenarios, enabling learners to practice diagnosis and treatment planning in a safe environment.Students can interact with virtual patients, review symptoms, order tests, and make treatment decisions while receiving guidance throughout the learning process.<h2>How AR Is Reshaping Hands-On Medical Training</h2>Augmented Reality overlays digital information onto the physical world, creating highly immersive educational experiences.Unlike traditional textbooks or videos, AR enables learners to visualize anatomy and procedures in three dimensions.<h3>Immersive Anatomy Education</h3>Understanding human anatomy is fundamental but often challenging.AR applications allow students to:<ul><li>Explore interactive 3D anatomical models.</li><li>Visualize organs from multiple angles.</li><li>Observe physiological processes dynamically.</li><li>Study complex structures without cadavers.</li></ul>Students can interact with holographic organs and systems, leading to deeper comprehension and improved engagement.<h3>Procedure and Surgical Simulation</h3>AR-based simulation platforms are increasingly used to train clinicians on complex procedures before they enter operating rooms.Examples include:<ul><li>Minimally invasive surgery training.</li><li>Catheter insertion practice.</li><li>Orthopedic procedure simulation.</li><li>Ultrasound-guided intervention training.</li></ul>By overlaying digital guidance onto physical models, AR enables repeated practice without risk to patients.<h3>Remote Collaboration and Mentoring</h3>Geographical barriers remain a significant challenge across APAC, particularly in rural and underserved areas.AR-enabled remote collaboration allows experts to guide trainees from different locations in real time.Specialists can:<ul><li>Annotate directly on the trainee's field of view.</li><li>Demonstrate procedures remotely.</li><li>Provide step-by-step guidance during simulations.</li><li>Support continuing medical education programs.</li></ul>This capability is particularly valuable in regions where specialist resources are limited.<h2>Innovation Trends Across Asia-Pacific</h2>The APAC region is becoming a global hub for digital health innovation, with governments, universities, and healthcare providers actively investing in advanced learning technologies.<h3>Singapore: Building Smart Healthcare Talent</h3>Singapore continues to lead digital healthcare adoption in Southeast Asia. Academic institutions and healthcare organizations are increasingly incorporating AI-driven simulations, virtual learning environments, and immersive technologies into medical training programs.The country's strong digital infrastructure and commitment to healthcare innovation make it a key market for next-generation medical education solutions.<h3>Australia: Expanding Simulation-Based Learning</h3>Australia has long been recognized for its advanced simulation centers. Universities and teaching hospitals are increasingly adopting AR and AI technologies to enhance clinical skills training, improve patient safety, and support remote education initiatives.The growing use of virtual patients and immersive procedural training reflects a broader shift toward competency-based education.<h3>Japan: Integrating Robotics, AI, and AR</h3>Japan's aging population and healthcare workforce challenges are accelerating investments in advanced training technologies.Medical institutions are exploring combinations of AI, robotics, AR, and mixed reality to train clinicians more efficiently while supporting continuous professional development.<h3>South Korea: Accelerating Digital Medical Innovation</h3>South Korea's strong technology ecosystem has fueled the rapid adoption of digital learning solutions.Medical schools and hospitals are leveraging AI-powered educational platforms and immersive visualization tools to enhance surgical education and precision medicine training.<h3>Emerging Opportunities in Southeast Asia</h3>Countries such as Vietnam, Thailand, Malaysia, and Indonesia are increasingly investing in digital health ecosystems.As healthcare demand rises, scalable and cost-effective training technologies offer significant potential to:<ul><li>Expand healthcare workforce capacity.</li><li>Improve training accessibility in remote regions.</li><li>Standardize clinical education.</li><li>Support continuing medical education initiatives.</li></ul><h2>Challenges to Adoption</h2>Despite strong momentum, organizations must address several challenges when implementing AI and AR in medical education.<h3>Data Privacy and Security</h3>Educational platforms handling learner and clinical data must comply with local regulatory requirements and maintain robust cybersecurity measures.<h3>Integration with Existing Systems</h3>Many institutions operate legacy learning management systems and hospital infrastructures that may require modernization or interoperability enhancements.<h3>Content Development Complexity</h3>Developing clinically accurate, high-quality immersive content requires close collaboration among healthcare professionals, educators, designers, and technology teams.<h3>Technology Accessibility</h3>Institutions must ensure that advanced learning technologies remain accessible, scalable, and cost-effective, particularly in resource-constrained settings.<h2>The Future of Medical Education in APAC</h2>The convergence of AI and AR is reshaping how healthcare professionals are educated across Asia-Pacific.Future learning environments are expected to become increasingly intelligent, immersive, and data-driven. Adaptive learning platforms, mixed reality simulations, digital twins, and automated competency assessments will likely become standard components of medical education ecosystems.As healthcare continues to evolve, organizations that invest in these technologies today will be better positioned to build highly skilled, future-ready workforces capable of delivering better patient outcomes.

AI + AR in Medical Education: Innovation Trends Across Asia-Pacific

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<h2>How Organizations Can Innovate with AI While Meeting Compliance, Security, and Trust Requirements</h2>AI is rapidly transforming industries worldwide. From automating clinical documentation in healthcare to accelerating risk assessment in financial services and improving quality control in manufacturing, AI is becoming a critical business capability.However, organizations operating in regulated industries face a unique challenge: how to harness the power of AI while maintaining strict security, compliance, privacy, and governance standards.For sectors such as healthcare, banking, insurance, life sciences, telecommunications, and government services, AI adoption cannot come at the expense of regulatory obligations. Security must be built into the foundation of every AI application, not added as an afterthought.This is why organizations are increasingly shifting their focus from simply deploying AI models to building secure, enterprise-grade AI solutions that are designed for compliance from day one.<h2>AI Introduces New Security Challenges</h2>Unlike traditional software, AI systems often process large volumes of sensitive data and generate dynamic outputs. This creates new risks, including data leakage, unauthorized access, model manipulation, and compliance violations.For example, healthcare AI applications may handle patient records, while financial AI systems analyze customer transactions and personal information. Any security failure can lead to regulatory penalties, reputational damage, and loss of customer trust.This makes security a fundamental requirement rather than an afterthought.<h2>Strong Data Governance Comes First</h2>Secure AI starts with strong data governance. Organizations need clear policies for how data is collected, stored, accessed, and used throughout the AI lifecycle.In regulated environments, maintaining control over sensitive information is critical. Effective governance helps ensure compliance, improves transparency, and reduces the risk of data misuse.Many AI initiatives succeed or fail based on the quality and governance of their data rather than the sophistication of the model itself.<h2>Embedding Security Throughout the AI Lifecycle</h2>Security should be integrated into every stage of AI development, from design and training to deployment and ongoing operations.Modern MLOps and LLMOps practices help organizations automate security checks, monitor model behavior, and maintain compliance without slowing innovation. By adopting a security-by-design approach, teams can identify risks early and build more resilient AI solutions.<h2>Transparency Builds Trust</h2>In regulated industries, organizations often need to explain how AI-driven decisions are made. Whether supporting clinical recommendations or fraud detection, AI systems must be transparent and auditable.Monitoring, logging, and governance mechanisms help organizations maintain visibility into model behavior while meeting regulatory expectations. Transparency not only supports compliance but also increases confidence among users, customers, and regulators.<h2>The Future of Enterprise AI</h2>As AI adoption grows, security and governance are becoming key differentiators. Organizations are moving beyond isolated AI experiments and investing in enterprise-grade platforms that combine data protection, access controls, model governance, and continuous monitoring.At the same time, responsible AI principles such as fairness, accountability, and explainability are becoming essential components of AI strategies.<h2>Conclusion</h2>Building AI applications for regulated industries requires far more than selecting the right model or technology stack. Success depends on creating secure, compliant, and governable systems that protect sensitive data, meet regulatory requirements, and maintain stakeholder trust.By adopting security-by-design principles, implementing robust governance frameworks, and integrating secure MLOps practices, organizations can confidently deploy AI solutions that drive business value without compromising compliance or security.As AI continues to reshape industries, the organizations that prioritize trust, security, and responsible innovation will be the ones that unlock its full potential.

Building Secure AI Applications for Regulated Industries

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Pharma 5.0: How ALTEN accelerates digital transformation to cut time to market?The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality. Digital transformation powered by AI is reshaping how pharma companies operate, from clinical trials to quality control.&nbsp; &nbsp; For François Portier, Digital Transformation and Industrial Excellence Expert at ALTEN, the shift is clear: “Today, AI isn’t just an option; it’s the key to unlocking efficiency and innovation in pharma.”But how can AI bridge the gap between data overload and actionable insights and what role does ALTEN play in this transition?The pharma industry’s digital dilemmaPharma’s traditional processes reliant on manual documentation, siloed data, and human monitoring are no longer sustainable. 75% of pharma companies are small enterprises, many still using pen-and-paper systems. Meanwhile, larger firms struggle to integrate AI into existing workflows.Key pain points:Time-consuming compliance: Certification and deviation report often start from scratch, delaying critical decisions.Inefficient quality control: Manual inspections (e.g., visual checks for bottle defects) are slow and prone to error.Data underutilisation: Historically, 70% of pharma data went unused until AI made it actionable."Five years ago, we focused on automation, today, we’re deploying customised and flexible processes with AI solutions", notes François Portier.ALTEN’s approach: AI as a Business acceleratorALTEN collaborates with partners and customers to deploy AI where it matters most, reducing time to market while ensuring compliance and quality.Generative AI is reshaping how pharmaceutical engineers handle documentation. By auto-filling templates with historical data, it cuts report drafting time from two hours to just 20 minutes, while automating compliance checks and flagging regulatory gaps instantly.&nbsp;"AI doesn't replace expertise, it enhances it", notes François Portier: engineers stay focused on high-value decisions while AI handles the rest.On the production floor, computer vision detects defects in real time with greater accuracy than manual inspection. Predictive analytics then simulates clinical trial parameters to reduce failure risks before testing begins.&nbsp;“With only 14% of trials reaching success, AI helps prioritise the most promising paths," François Portier emphasises.ALTEN tailors its approach to each organisation's level of digital maturity. Smaller firms begin with data digitisation using no-code tools, while larger enterprises deploy agentic AI to unify operational and IT data. There is no single model: the right solution depends on where a company stands today and where it needs to go.The human-AI partnership: skills for the futureAI’s rise doesn’t diminish human roles, it redefines them. ALTEN emphasises upskilling teams to:Combine hard skills (e.g., IoT/robotics programming) with industry knowledge.Develop soft skills like problem-solving and project ownership. "The future engineer is strategic, not just technical", François Portier asserts."For pharma, the message is clear: AI isn’t a threat, it’s the tool to deliver treatments faster, more safely, and more effectively, with greater personalisation for patients."&nbsp;About our expertFrançois PortierDigital Transformation &amp; Industrial Excellence Expert at ALTEN FranceFrançois Portier drives AI-powered innovation in pharma, helping companies reduce time to market while ensuring quality and compliance. With expertise in generative AI, computer vision, and predictive analytics, he tailors solutions to each organisation’s digital maturity, from low-code tools for small firms to agentic AI for large enterprises.A firm believer in human-AI collaboration, François focuses on upskilling teams to blend technical skills with strategic thinking.Connect with François Portier: <a href="https://fr.linkedin.com/in/francoisportier/fr">LinkedIn Profile</a>&nbsp;

The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality. Digital transformation powered by AI is reshaping how pharma companies operate, from clinical trials to quality control. 
 
For François Portier, Digital Transformation and Industrial Excellence Expert at ALTEN, the shift is clear: "Today, AI isn’t just an option; it’s the key to unlocking efficiency and innovation in pharma."

Pharma 5.0: How digital transformation cuts time to market

The pharmaceutical industry faces a critical challenge: bringing life-saving treatments to market faster without compromising quality..

How ALTEN accelerates digital transformation to cut time to market?

how-alten-accelerates-digital-transformation-to-cut-time-to-market

In 2026, AI governance is no longer optional, it has become a strategic business priority. According to recent industry research, 54% of IT leaders now consider AI governance as a critical enterprise risk, up significantly from 29% just two years ago (Kiteworks, 2026). In Vietnam, the introduction of the Law on Artificial Intelligence, effective from March 1, 2026, marks a major milestone in the country's digital transformation journey. The new regulatory framework requires organizations to move beyond AI experimentation and adopt a more structured approach aligned with the principles of Sovereign AI, enabling both regulatory compliance and new sources of competitive advantage.1. Overview of Sovereign AI and AI GovernanceAI Governance refers to the framework of policies, processes, standards, and controls designed to ensure that AI systems are developed and deployed responsibly, transparently, ethically, and in alignment with business objectives. Unlike traditional IT governance, which primarily focuses on managing static infrastructure and systems, AI governance addresses the dynamic nature of AI models that continuously learn, evolve, and influence business decisions over time.Sovereign AI describes an organization's or nation's ability to maintain control over its AI ecosystem, including data, computing infrastructure, and AI models, rather than relying entirely on foreign platforms and services. The objective is to strengthen digital sovereignty, ensure that critical data remains under local control, and enable strategic decision-making within national or organizational boundaries.2. The global AI regulatory landscape in 2026The year 2026 represents a significant turning point in the global enforcement of AI regulations.The EU AI actThe European Union's AI Act, the world's first comprehensive AI regulatory framework, will begin enforcing key obligations for General-Purpose AI (GPAI) models from August 2nd, 2026. The regulation introduces stringent requirements around transparency, accountability, and risk management, creating what many experts describe as the "Brussels effect," where global organizations voluntarily align with EU standards regardless of location.The rise of sovereignty initiativesCountries such as the United States and South Korea have introduced major executive orders and legislative initiatives throughout late 2025 and early 2026 to strengthen control over national AI capabilities. These efforts focus on protecting domestic data through Sovereign Cloud architectures while enhancing national competitiveness in AI development and deployment.Governance as a strategic obligationAI governance is no longer viewed solely as a compliance exercise. Increasingly, organizations recognize it as a core operational strategy that helps build trust with customers, partners, investors, and regulators.3. AI regulation in VietnamThe Law on Artificial Intelligence (Law No. 134/2025/QH15), effective from March 1, 2026, establishes a risk-based regulatory framework that aligns with international standards while addressing the country's unique regulatory and economic context.Three-tier risk classification framework<ul><li>High-risk AI systems: AI systems that may cause significant harm to human life, health, legal rights, public interests, national interests, or national security.</li><li>Medium-risk AI systems: AI systems capable of influencing, misleading, or manipulating users who may not realize they are interacting with an AI system or consuming AI-generated content.</li><li>Low-risk AI systems: AI systems that do not fall under the high-risk or medium-risk categories.</li></ul>Post-market supervision approachOrganizations are not required to obtain prior approval for low-risk AI applications. However, they must conduct internal safety assessments, maintain relevant documentation, and be prepared to demonstrate compliance when requested by regulators.Compliance timelineFor AI systems already in operation before the law takes effect:<ul><li>Healthcare, education, and financial services AI systems must achieve compliance within 18 months from the effective date.</li><li>AI systems in all other sectors must achieve compliance within 12 months from the effective date.</li></ul>4. Opportunities and challenges for businessesThe introduction of the Law on Artificial Intelligence in Vietnam is expected to reshape the country's AI ecosystem by creating both new growth opportunities and additional compliance responsibilities for businesses.From an opportunity perspective, the new regulatory framework provides stronger institutional support for AI innovation and commercialization. By formally recognizing AI models, algorithms, and data assets as legitimate business assets, the law creates new pathways for investment, fundraising, strategic partnerships, and intellectual property capitalization. At the same time, organizations engaged in AI development may benefit from enhanced government incentives, including tax preferences, technology funding programs, and access to national digital infrastructure.The government's broader commitment to AI development is also reflected in initiatives such as the National AI Development Fund, open data platforms, and shared computing resources. These initiatives have the potential to lower entry barriers for startups and SMEs while accelerating innovation across industries. In addition, regulatory sandbox mechanisms will allow organizations to experiment with emerging AI applications within controlled environments, reducing regulatory uncertainty and encouraging responsible innovation.However, these opportunities come with new challenges. As AI governance requirements become more strict, organizations will need to invest in risk management frameworks, monitoring systems, documentation processes, and governance capabilities to ensure compliance. For many businesses, the operational and financial costs associated with these requirements may be significant.Furthermore, Vietnam continues to face structural challenges related to AI readiness, including limited access to high-performance computing resources, fragmented data ecosystems, and a shortage of experienced AI and data professionals. Addressing these gaps will be critical for organizations seeking to fully capitalize on the opportunities created by the country's evolving AI landscape.5. A roadmap for building AI governanceTo prepare for the 2026 regulatory landscape, organizations should consider the following phased approach.Phase 1: Establish the foundationCreate a dedicated AI Governance function involving executive leadership, legal teams, risk management, and IT departments. Conduct a comprehensive inventory of all AI applications and classify them according to risk levels.Phase 2: Build governance processesDevelop acceptable-use policies, define risk thresholds, establish escalation procedures, and implement emergency controls to address AI-related incidents.Phase 3: Monitor and optimizeDeploy tools to monitor model performance, bias, drift, and compliance. Integrate AI governance into the broader Enterprise Risk Management (ERM) framework to ensure ongoing oversight and continuous improvement.6. The evolving role of technology companiesAs AI regulations become increasingly embedded in business operations, the role of technology companies is expanding beyond the development and deployment of AI solutions. In the past, competitive advantage was often defined by an organization's ability to integrate AI into products, automate processes, or enhance customer experiences. Today, success increasingly depends on the ability to deliver AI systems that are not only effective but also transparent, secure, compliant, and accountable throughout their lifecycle.This shift places new responsibilities on technology providers. Organizations that develop, integrate, or operate AI systems for clients must now consider governance requirements from the earliest stages of design through deployment, monitoring, and ongoing operation. As a result, AI governance is becoming a foundational component of enterprise architecture rather than a compliance layer applied after implementation.In this environment, capabilities such as cloud infrastructure, data engineering, cybersecurity, and enterprise governance become critical enablers of responsible AI adoption. The ability to connect these capabilities into a cohesive operating model may ultimately become as important as AI model development itself.From VMO's perspective, this transformation reflects a broader trend already emerging across global markets. As organizations accelerate AI adoption, projects increasingly require an integrated approach that combines AI, data, cloud, security, and operational governance. This aligns closely with VMO's multidisciplinary capabilities and experience delivering complex digital transformation initiatives for international clients.Looking ahead, the rise of Sovereign AI is expected to generate growing demand for AI infrastructure, data platforms, governance frameworks, integration services, and consulting expertise. Beyond regulatory compliance, this creates an opportunity for technology companies such as VMO to support organizations in building scalable, trustworthy, and business-driven AI ecosystems while strengthening Vietnam's position within the global AI value chain.ConclusionSovereign AI and AI Governance are more than regulatory requirements, they are becoming strategic differentiators in the next phase of digital transformation. Organizations that proactively align with the Law on Artificial Intelligence while leveraging the incentives and opportunities created by the new regulatory framework will be better positioned to build trust, improve operational resilience, and create sustainable competitive advantages.As AI adoption continues to accelerate, investing in governance today may be one of the most important steps organizations can take to ensure long-term success in the digital economy of tomorrow.

In 2026, AI governance is no longer optional, it has become a strategic business priority. According to recent industry research, 54% of IT leaders now consider AI governance as a critical enterprise risk, up significantly from 29% just two years ago (Kiteworks, 2026). In Vietnam, the introduction of the Law on Artificial Intelligence, effective from March 1, 2026, marks a major milestone in the country's digital transformation journey. The new regulatory framework requires organizations to move beyond AI experimentation and adopt a more structured approach aligned with the principles of Sovereign AI, enabling both regulatory compliance and new sources of competitive advantage.

AI Governance: Preparing Vietnamese Businesses

In 2026, AI governance is no longer optional, it has become a strategic business priority. According to recent industry research..

ai-governance-preparing-vietnamese-businesses

Hanoi, Vietnam - June 2026VMO, an ALTEN Group company, today announced a leadership transition that marks an important milestone in its next phase of growth and development. The transition comes as VMO continues to expand its global footprint, strengthen international collaboration, and accelerate its long-term growth strategy.Effective June 15, 2026, Ms. Nguyen Khanh Diep (Jamie Nguyen) will assume the role of Chief Executive Officer (CEO) of VMO. Following the transition, Mr. Hoang Tuan Hai will take on the role of Chairman of the Founding Board and Member of the Board of Directors, continuing to contribute to the company’s long-term strategic direction and governance.Over nearly 14 years of growth, VMO has continuously evolved to meet changing market demands, expand its global presence, and strengthen its position as a trusted technology partner. As part of the ALTEN Group, VMO is entering a new chapter focused on scaling its capabilities, strengthening international collaboration, and creating greater value for customers worldwide. This leadership transition reflects the company’s commitment to building a sustainable organization while preparing for its next stage of development.Having played a key role in VMO’s growth journey, Jamie Nguyen brings extensive leadership experience, deep operational expertise, and a strong understanding of the company’s culture, people, and customers. As CEO, she will lead VMO’s business operations and strategic execution, driving the organization forward in an increasingly dynamic and competitive market.<figure class="image"><img src="https://vmo-ho-web-global.s3.ap-southeast-1.amazonaws.com/vmogroup-global/uploads/1781515570948-DSC00557.jpg"></figure>Biography of Jamie NguyenJamie Nguyen joined VMO in April 2019 and has held a series of leadership positions across the organization, including Head of Sales, Sales Director, CEO of VMO Global, and Vice CEO of VMO Holdings, prior to her appointment as Chief Executive Officer of VMO.She graduated from the Specialized Informatics Program at Hanoi National University of Education High School for Gifted Students, earned a Bachelor's degree from the Banking Academy of Vietnam, and later obtained an MBA from Ritsumeikan Asia Pacific University, Japan.Throughout her tenure at VMO, Jamie has contributed to the company's business growth, international expansion, and organizational development, helping strengthen VMO's position as a trusted technology partner in global markets.Entering this new chapter, Mr. Hoang Tuan Hai will remain actively engaged in supporting Jamie Nguyen and the leadership team on strategic initiatives that will drive VMO’s long-term growth.Mr. Hoang Tuan Hai stated:&nbsp;“Jamie Nguyen is the right leader to guide VMO through this next chapter. Throughout her journey with the company, she has played a critical role in many important growth milestones, demonstrating strong leadership, business acumen, and a deep understanding of our people, customers, and culture. Her proven track record, commitment to excellence, and ability to build and develop high-performing teams have earned the trust and respect of colleagues across the organization. I am confident that under her leadership, VMO will continue to grow stronger, adapt successfully to the opportunities and challenges ahead, and reach new levels of achievement.”Ms. Jamie Nguyen stated:&nbsp;“I deeply appreciate what generations of VMOers have built over the years, and I am genuinely excited about the opportunities that lie ahead. I look forward to working together with all of you and ALTEN Group to continue building a stronger VMO, creating greater value for our customers, developing new capabilities, and making VMO a place that we are always proud to be part of.”This leadership transition reflects VMO’s ongoing commitment to strengthening its leadership foundation, fostering innovation, and creating sustainable value for customers, employees, and partners. Backed by the global expertise and scale of the ALTEN Group, VMO remains focused on accelerating growth, delivering excellence to its customers, and expanding its impact across international markets.

VMO, an ALTEN Group company, today announced a leadership transition that marks an important milestone in its next phase of growth and development. The transition comes as VMO continues to expand its global footprint, strengthen international collaboration, and accelerate its long-term growth strategy.

VMO ANNOUNCES CEO TRANSITION AND LEADERSHIP EVOLUTION

VMO, an ALTEN Group company, today announced a leadership transition that marks an important milestone in its next phase of growth and development.

vmo-announces-ceo-transition-and-leadership-evolution

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On April 1, 2021, VMO Holdings Technology Joint Stock Company (VMO) held a Ceremony to announce its Vision, Mission &amp; Core Values which has been solidified during the past 10 years of establishment and development. On that enduring journey full of proud milestones was the great leadership of the Board of Directors, in alignment with the consensus of all the members of VMO.&nbsp;Along with the outstanding development and growth, VMO embraces the goal of meeting an increasingly rigorous requirements of the IT market, conquering the satisfaction of significant customers in various large-scale projects. Above all lies the ultimate development goal of VMO, closely tied with its core values, lofty mission, and new vision to bring VMO to a new position, increase its influence and spread more good values to the community.In parallel with the investment and development of human resources and technology, VMO clearly understand the desires and ideal that company needs to implement to make VMO a global technology company. VMO officially announce its Mission, Vision &amp; Core values Statement:&nbsp;OUR VISION&nbsp;To be recognized as a Global Leading IT Company<ul><li>To actualize the innovative idea of clients around the world with professional software development and business consultation services.</li></ul>OUR MISSIONFrom Idea to Reality, From Goodwill to Impact<ul><li>VMO turn&nbsp;the&nbsp;ideas of the clients&nbsp;into valuable products that actively contribute for the betterment of the society.</li></ul>OUR CORE VALUESDesire<ul><li>Desire is the aspiration to achive greatness. We desire, we change, we thrive.</li></ul>Transparency<ul><li>&nbsp;VMO Holdings embraces transparency. Internally, we make sure that every voices are listened. To clients, we build the relationship with goodwill and trust. Transparency is the foundation of sustainable development.</li></ul>Conscientiousness<ul><li>We treat each task&nbsp;with&nbsp;passion and enthusiasm. Dedication is the secret of outstanding efficiency.</li></ul>Synergy&nbsp;<ul><li>We&nbsp;are group&nbsp;of&nbsp;different personalities with a same will&nbsp;and common goal. Synergies is the engine of great teamwork.</li></ul>VMO Holdings Technology Joint Stock Company hopes that a new vision, mission, and core values will serve to achieve company’s development goals, bring company to a new position, upgrade its corporate culture, and create useful values to contribute to the development of global humanity.

On April 1,  VMO officially announced vision, mission and Core values Statement

VMO ANNOUNCED VISION, MISSION, CORE VALUES

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On December 24, 2019, VMODEV Hanoi Technology Joint Stock Company officially established a branch of VMO Japan at 〒101-0047 Tokyo , Chiyoda-ku , Uchikanda, 2-14-12, Hoshiya 6th Building No 402, one of World's largest economic centers.&nbsp;Founded in 2012, VMODEV has over 8 years developing and accompanying many European and American businesses, successfully building many technological products from the concept stage to delivering to users, including the product reaches more than 15 million users worldwide.Quality, Flexibility, Speed are the core values that the leaders and employees of VMODEV have pursued for nearly 10 years. Identifying Japan as the next important market in the company's long-term development strategy, Mr. Hoang Tuan Hai, CEO of VMODEV said: “The Japanese IT market is a large market with strict requirements for quality. We believe that by understanding the culture of our team in Japan, VMODEV can completely bring success to Japanese businesses, such as the satisfaction we bring to clients in the Europe and America, EU markets”.In Japan, VMODEV wishes to assist clients in deploying digital business models, as well as applying IT platforms and new technologies such as AI, Cloud, RPA ... to improve productivity and efficiency for current business models. VMODEV will provide high quality IT human resources for Japanese businesses. It is expected that after Japan, VMODEV will continue to expand more branches in countries such as the USA, Singapore, Korea ... in the near future.&nbsp;More information about VMODEVVMODEV was founded in 2012 by technology enthusiasts and desires to contribute and bring practical values to society. Currently the company has 4 working offices and its headquarters are located in Hanoi, Vietnam. Over 8 years of working with many partners in Europe, America, EU, Asia ... VMODEV has developed more than 300 projects with clients from 11 countries. The products we design and deploy reach more than 45 million users globally.&nbsp;Contact information<figure class="table"><table><tbody><tr><td>VMODEV HANOI TECHNOLOGY JOINT STOCK COMPANYAddess: 15th Floor, TTC Tower, 19 Duy Tan st., Dich Vong Hau ward., Cau Giay dist., Hanoi 100000Phone number: +84 24 3312 0103Website: <a href="https://www.vmodev.com/">https://www.vmodev.com</a>Email: <a href="mailto:info@vmodev.com">info@vmodev.com</a></td><td>VMO JAPAN JOINT STOCK COMPANYAddress: 〒101-0047 Tokyo , Chiyoda-ku , Uchikanda, 2-14-12, Hoshiya 6th Building No 402Phone number: 03-4400-2818Website: <a href="https://www.vmodev.jp/">https://www.vmodev.jp</a>Email: <a href="mailto:infojp@vmodev.com">infojp@vmodev.com</a></td></tr></tbody></table></figure>&nbsp;

On December 24, 2019, VMODEV officially established a branch of VMO Japan

VMODEV OFFICIALLY ESTABLISHED A BRANCH IN JAPAN

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Job Description: We’re seeking for Pre-senior/Senior BA/DA to join our team&nbsp;Key Responsibilities<ul><li>Gather, analyse and formalise user’s business requirements and processes, evaluate on feasibility of implementation and manage scope of project.</li><li>Prepare project documentation such as Requirement Specifications/Use Case Specifications etc.</li><li>Adhere to project scope, update requirement traceability matrix, inform and record out-of-scope issues.</li><li>Develop technical design specification and translate technical design into process/program specification. Involve in the design review session.</li><li>Make changes to configurable items, which include hardware, software, documentation, etc.</li><li>Assist in the integration testing, system testing, User Acceptance Test &amp; implementation activities.</li><li>Prepare user manual and operations manual, and plan &amp; facilitate training of users and operators.</li><li>Provide post implementation support (including production support and service requests).</li><li>Escalate and discuss critical issues such as scope creep with the product managers.</li><li>Conduct requirement gathering sessions. Conduct gap analysis of current business process to identify improvement opportunities.</li><li>Collaborate with vendors to address integration challenges, fostering seamless system operation and reliability across systems used in the company.</li><li>Collaborate with stakeholders to enhance systems processes, ensuring alignment with overall business objectives.</li><li>Constantly explore opportunities to enhance systems and explore new tools in the market focusing on improving the efficiency and experience of users.</li><li>Provide technical training to a large audience from the user's perspective.</li><li>In-Depth Performance and Data Analysis for the system and data used by users.</li><li>Support multiple product and project streams, along with varying resources, across the team to ensure on time and quality delivery of all solutions.</li></ul>

Business Analyst

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About the Role&nbsp;:&nbsp;Responsible for managing end-to-end recruitment for positions in Telecom, Embedded, Wireless, C/C++, Network, and other specialized technical fields. Proactively develop candidate sources, perform talent mapping, and provide recruitment consultation to support the company’s strategic workforce needs.Key Responsibilities1. Recruitment<ul><li>Manage recruitment activities for positions including Telecom Engineer, Embedded Engineer, Wireless Engineer, C/C++ Engineer, Network Engineer, and related technical roles.&nbsp;</li><li>Handle the full recruitment lifecycle, including sourcing, screening, interviewing, offering, and onboarding.&nbsp;</li><li>Ensure achievement of recruitment KPIs in terms of quality, quantity, and turnaround time.&nbsp;</li></ul>2. Talent Mapping &amp; Market Intelligence<ul><li>Conduct talent mapping of target companies in Telecom, Embedded, and technology-related fields.&nbsp;</li><li>Research the talent market, competitors, and recruitment trends.&nbsp;</li><li>Build and maintain a pipeline of potential candidates to support long-term hiring needs.&nbsp;</li></ul>3. Stakeholder Management<ul><li>Work closely with Hiring Managers and business units to understand recruitment requirements.&nbsp;</li><li>Provide consultation on talent market insights, candidate availability, and appropriate recruitment strategies.&nbsp;</li><li>Track, update, and report recruitment progress on a regular basis.&nbsp;</li></ul>4. Sourcing &amp; Networking<ul><li>Proactively expand sourcing channels, networking activities, and referral networks.&nbsp;</li><li>Build candidate communities and maintain relationships with potential candidates in the market.</li></ul>

Talent Acquisition Specialist

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We are seeking a talented Data Scientist / AI Engineer with strong expertise in Generative AI, NLP, and LLM-based applications. The ideal candidate will have hands-on experience building end-to-end GenAI workflows and applying advanced AI technologies to solve real-world business problems.&nbsp;In This Role, You Will:&nbsp;<ul><li>Design and develop end-to-end Generative AI and NLP solutions.</li><li>Build and optimize LLM, RAG, Agentic AI, and NLP applications for business use cases.</li><li>Perform prompt engineering and develop scalable GenAI workflows.</li><li>Develop production-ready AI systems using Python and PySpark.</li><li>Collaborate closely with business and technical teams to deliver AI solutions with measurable impact.</li><li>Clearly communicate technical findings and recommendations to stakeholders.</li></ul>

Data Scientist - AIS

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Summary:&nbsp; The Data Scientist role focuses on building propensity models and sizing market opportunities for VMO project with banking clients. This hybrid position requires a blend of data science and engineering skills to create production-grade pipelines. The role is pivotal in driving sales strategy through data-driven outputs. Candidates should have a strong background in Python and SQL, along with proven experience in propensity modeling.Propensity Modeling &amp; Ranking: &nbsp; &nbsp; Predict CTR and engagement probability &nbsp; &nbsp; Use models like XGBoost / LightGBM &nbsp; &nbsp; Optimize ranking using NDCG, MRR, Precision@KFeature Engineering: &nbsp; &nbsp; Build features from user behavior, interaction signals, and context &nbsp; &nbsp; Handle sparse and noisy dataCold Start Handling: &nbsp; &nbsp; Design strategies for new users and new offers &nbsp; &nbsp; Implement hybrid and fallback approachesBias Handling: &nbsp; &nbsp; Mitigate popularity and exposure bias &nbsp; &nbsp; Implement diversity and re-ranking strategiesModel Evaluation: &nbsp; &nbsp; Define and track CTR, conversion, NDCG, AUC &nbsp; &nbsp; Continuously improve engagement metricsScalability &amp; Deployment: &nbsp; &nbsp; Build systems for millions of users &nbsp; &nbsp; Enable real-time or near real-time inference

AI Engineer - onsite

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<ul><li>Develop, execute, and maintain test plans, test cases, and test scripts for a digital platform.</li><li>Perform functional, regression, performance, integration, and user acceptance testing (UAT).</li><li>Collaborate with developers, business analysts, and designers to understand requirements and ensure test coverage.</li><li>Identify, document, and track defects using issue tracking tools (e.g., JIRA).</li><li>Validate bug fixes and perform re-testing as needed.</li><li>Participate in sprint planning, stand-ups, and retrospectives in an Agile environment.</li><li>Ensure digital products meet accessibility standards and cross-browser/device compatibility.</li><li>Develop and support automation testing efforts and contribute to test automation frameworks.</li><li>Provide QA sign-off for releases and deployments.</li></ul>

FULLSTACK TESTER (AUTOMATION & MANUAL) - ENG GOOD - DU33

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About the Role As an HR Business Partner (HRBP) Expert, you will act as a strategic advisor to key business units (Operations, Delivery, Sales, etc.), partnering closely with leadership to drive organizational effectiveness, talent development, and business performance. You will play a critical role in aligning people strategies with business objectives while fostering a high-performance and purpose-driven culture. Recruitment Requirements Key Responsibilities<ul><li>Partner with business leaders to design and implement people strategies that drive performance, engagement, and growth.</li><li>Advise on organizational design, workforce planning, and headcount management aligned with business priorities.</li><li>Collaborate with Talent Acquisition and L&amp;D teams to attract, develop, and retain key talents.</li><li>Lead talent management initiatives, including performance management, succession planning, and leadership development.</li><li>Drive career development frameworks, competency mapping, and capability building programs.</li><li>Act as a trusted advisor to leaders on employee relations and complex people matters.</li><li>Ensure compliance with local labor laws and internal policies.</li><li>Champion and embed company culture, ensuring alignment between organizational values and business practices.</li><li>Leverage HR data and analytics (attrition, engagement, performance) to generate insights and support decision-making.</li><li>Continuously improve HR processes to enhance efficiency and employee experience.</li></ul>

HR Business Partner Team Leader

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About the RoleWe are looking for a Senior DevOps Engineer with strong expertise in AWS, Kubernetes, and CI/CD to build and operate scalable cloud-native platforms. You will work closely with development teams to automate infrastructure, optimize deployment processes, and ensure system reliability, security, and performance.Responsibilities<ul><li>Design and manage scalable, secure, and highly available AWS infrastructure.</li><li>Build and maintain Kubernetes environments (EKS or self-managed).</li><li>Develop and optimize CI/CD pipelines for automated deployments.</li><li>Implement Infrastructure as Code using Terraform or CloudFormation.</li><li>Collaborate with engineering teams on cloud-native and microservices architectures.</li><li>Monitor system performance and ensure reliability through logging, metrics, and alerting.</li><li>Apply security best practices across infrastructure and deployment pipelines.</li><li>Participate in Agile development processes and technical discussions.</li><li>Create and maintain technical documentation.</li></ul>

DevOps Engineer (Tokyo, Japan)

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<ul><li style="text-align:justify;">Develop and maintain backend systems and APIs using Python Django.</li><li style="text-align:justify;">Build and support frontend applications using Angular.</li><li style="text-align:justify;">Design, develop, and optimize scalable, secure, and high-performance applications.</li><li style="text-align:justify;">Work with PostgreSQL for database design, integration, and optimization.</li><li style="text-align:justify;">Implement authentication and authorization solutions using OAuth2 and OIDC.</li><li style="text-align:justify;">Write clean, maintainable code and ensure software quality through testing and code reviews.</li><li style="text-align:justify;">Participate in system design discussions and contribute to technical solutions.</li><li style="text-align:justify;">Collaborate with cross-functional teams in an Agile environment.</li><li style="text-align:justify;">Support troubleshooting, performance improvements, and mentoring team members when needed.</li></ul>

Fullstack Developer (Python Django, Angular - English Fluent)

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Summary:&nbsp; The Data Scientist role focuses on building propensity models and sizing market opportunities for VMO project with banking clients. This hybrid position requires a blend of data science and engineering skills to create production-grade pipelines. The role is pivotal in driving sales strategy through data-driven outputs. Candidates should have a strong background in Python and SQL, along with proven experience in propensity modeling.<ol><li>Propensity Modeling &amp; Ranking: &nbsp; &nbsp; Predict CTR and engagement probability &nbsp; &nbsp; Use models like XGBoost / LightGBM &nbsp; &nbsp; Optimize ranking using NDCG, MRR, Precision@K</li><li>Feature Engineering: &nbsp; &nbsp; Build features from user behavior, interaction signals, and context &nbsp; &nbsp; Handle sparse and noisy data</li><li>Cold Start Handling: &nbsp; &nbsp; Design strategies for new users and new offers &nbsp; &nbsp; Implement hybrid and fallback approaches</li><li>Bias Handling: &nbsp; &nbsp; Mitigate popularity and exposure bias &nbsp; &nbsp; Implement diversity and re-ranking strategies</li><li>Model Evaluation: &nbsp; &nbsp; Define and track CTR, conversion, NDCG, AUC &nbsp; &nbsp; Continuously improve engagement metrics</li><li>Scalability &amp; Deployment: &nbsp; &nbsp; Build systems for millions of users &nbsp; &nbsp; Enable real-time or near real-time inference</li></ol>

AI Engineer ( Strong Python) - ENG GOOD

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Job Summary We are looking for 2 Senior Full-Stack Developers to join a cloud-native product team building enterprise-grade applications on Microsoft Azure. The role involves designing and implementing frontend interfaces, backend APIs, and microservices that integrate deeply with Azure cloud services. You will work across the full delivery lifecycle, from architecture decisions to CI/CD pipeline setup and production deployment.Key Responsibilities • &nbsp; &nbsp;Design and build responsive frontend applications using React or Angular, TypeScript, and chart libraries • &nbsp; &nbsp;Develop and maintain backend APIs and microservices using C# and .NET, following RESTful design principles • &nbsp; &nbsp;Implement background services, messaging queue patterns, and the Saga Pattern for distributed transaction management • &nbsp; &nbsp;Integrate applications with Azure services including Azure Front Door, API Management, Application Gateway, Azure Service Bus, Azure Redis, Azure Key Vault, and managed databases • &nbsp; &nbsp;Write and maintain CI/CD pipelines on Azure Pipelines, including build, test, scan, and deploy stages following DevSecOps practices • &nbsp; &nbsp;Apply security practices including SAST, dependency scanning, image scanning, secret management, and pipeline security gates • &nbsp; &nbsp;Containerize services using Docker with multi-stage builds; deploy and troubleshoot workloads on Azure Kubernetes Service (AKS) • &nbsp; &nbsp;Participate in Agile/Scrum ceremonies; understand and apply the 12 Cloud Native Factors in application design • &nbsp; &nbsp;Follow governance and security policies for Azure Resource Groups, service configurations, and user access control

Fullstack (.Net+ReactJS/Angular) DU33 - ENG GOOD

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<ul><li>Sourcing potential new customers in Japanese markets</li><li>Sell and meet sales target</li><li>Acting as a bridge between the customer and the project team</li><li>Bidding, negotiating and negotiating contracts, ensuring set KPI</li><li>Supporting customer during project implementation</li><li>Manage the contract</li><li>Get more in-depth training on information technology knowledge</li></ul>

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