Make an impact with NTT DATA Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive. 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 eval