Lead AI Solution Architect

Job description

Continue to make an impact with a company that is pushing the boundaries of what is possible. At NTT DATA, we are renowned for our technical excellence, leading innovations, and making a difference for our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can continue to grow, belong, and thrive. Your career here is about believing in yourself and seizing new opportunities and challenges. It’s about expanding your skills and expertise in your current role and preparing yourself for future advancements. That’s why we encourage you to take every opportunity to further your career within our great global team. About NTT DATA NTT DATA is a global innovator of business and technology services, supporting clients with consulting, cloud, data, artificial intelligence, applications, infrastructure, and managed services. Our international delivery network combines engineering capability, industry knowledge, and a strong partner ecosystem to help clients innovate and transform with confidence. About the Google Engineer Business The Google Engineer business delivers engineering and technology services for Google-oriented cloud, AI, data, and enterprise programs. The team works across NTT DATA delivery centers, customer organizations, and Google-aligned technical stakeholders to build secure, scalable, reliable, and production-ready solutions. This role contributes directly to that business by combining strong engineering practice with disciplined customer and delivery collaboration. Position Objective Lead the design and delivery of enterprise-grade AI and Generative AI solutions using Google Cloud and Vertex AI capabilities. Translate customer and business objectives into secure, scalable architectures; guide engineering teams through implementation; and ensure that research and proof-of-concept work becomes reliable , supportable production service. Key Responsibilities • Own end-to-end architecture for AI, GenAI, data, integration, and cloud-native solutions in Google Engineer business engagements. • Translate business requirements and customer priorities into reference architectures, solution blueprints, estimates, delivery roadmaps, and technical decisions. • Design production-ready LLM, RAG, agent, multimodal, document intelligence, and workflow automation solutions. • Apply Google Cloud and Vertex AI services such as Gemini, BigQuery , Cloud Storage, Cloud Run, GKE, Pub/Sub, Dataflow, Vertex AI Pipelines, Model Registry, IAM, and observability services where appropriate . • Define non-functional requirements for security, privacy, reliability, scalability, latency, maintainability, and cost efficiency. • Lead architecture reviews, design reviews, technical proposals, code-quality governance, and production-readiness assessments. • Guide the transition from research or PoC to production, including evaluation, guardrails, CI/CD, monitoring, incident readiness, and operational ownership. • Mentor AI, cloud, and software engineers; facilitate technical decisions; and remove engineering blockers across distributed teams. • Communicate technical trade-offs clearly to customers, delivery leaders, and non-technical stakeholders. • Identify delivery risks, dependencies, and opportunities for reusable platforms, accelerators, and engineering standards. Essential Qualifications Successful candidates will demonstrate the following combination of education, experience, and technical capability: • Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline. • At least 8 years of professional experience in solution architecture, software engineering, AI/ML engineering, cloud architecture, or a closely related field, including significant technical leadership experience. • Proven hands-on delivery of enterprise AI or Generative AI solutions from architecture and PoC through production operation. • Strong Google Cloud experience, including practical use of Vertex AI and related services; working knowledge of Gemini, BigQuery , Cloud Run or GKE, IAM, networking, data services, and observability. • Deep understanding of LLM application patterns, RAG, embeddings, vector search, agent orchestration, prompt engineering, model evaluation, safety controls, and AI governance. • Strong software engineering fundamentals in Python and API or microservice design, with the ability to review implementation quality and operational readiness. • Experience leading customer-facing technical discussions, architecture workshops, solution proposals, and delivery decisions in an international environment. • Professional English communication skills and the ability to collaborate effectively with distributed engineering and stakeholder groups. Preferred Qualifications • Google Cloud Professional Cloud Architect, Professional Machine Learning Engineer, or equivalent certification. • Experience with Google Agent Development Kit, TensorFlow, JAX, LangChain , LangGraph , or comparable frameworks. • Experience with responsible AI, security architecture, data governance, FinOps, and regulated enterprise environments. • English language proficiency or experience working with APAC -based stakeholders. Success Measures • Production solutions meet agreed reliability, security, quality, latency, and cost targets. • Architecture decisions are documented, reusable, and aligned with Google Cloud engineering standards. • PoCs are converted into viable production services with clear operational ownership. • Customer and delivery stakeholders receive timely , evidence-based technical guidance. • Engineering capability improves through mentoring, reusable assets, and consistent review practices. Benefits and Working Conditions • Competitive compensation package, with 100% salary during probation, subject to company policy and the employment offer. • Full social insurance contribution based on the applicable salary basis. • Annual performance bonus and salary review in line with company policy. • Premium healthcare insurance for employees and eligible family members from probation, subject to policy. • Annual health check-up and access to company-sponsored training, professional courses, and certification examinations. • Paid leave and public holidays in accordance with Vietnamese regulations and NTT DATA Vietnam policy. • Hybrid working model, flexible start time with manager approval, and a global environment with international collaboration. • Clear career development opportunities in cloud engineering, AI delivery, solution architecture, and technical leadership. Work Schedule • Monday to Friday, 08:00–12:00 and 13:00–17:00. • Flexible start time between 07:45 and 09:00 with manager approval. Work Locations • Hanoi: HITC Building, 239 Xuan Thuy Street, Hanoi, Vietnam. • Ho Chi Minh City: Opal Office Tower, 92 Nguyen Huu Canh Street, Ho Chi Minh City, Vietnam. Workplace type: Equal Opportunity Employer NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Accelerate your career with us. Apply today