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. •