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 Deliver secure, scalable, and measurable AI solutions using Google Cloud, Vertex AI, Gemini, and modern software engineering practices. This role covers the full engineering lifecycle: solution implementation, model and prompt evaluation, enterprise integration, production deployment, monitoring, troubleshooting, and continuous optimization.
Key Responsibilities • Design, develop, test, and deploy Generative AI applications and services using Gemini, Vertex AI, and suitable open-source or commercial models. • Build RAG pipelines covering document ingestion, chunking, embeddings, indexing, retrieval, grounding, citations, evaluation, and access control. • Develop AI agents and enterprise copilots that integrate with APIs, business systems, tools, and workflow automation.
• Implement model, prompt, and application evaluation; investigate quality, hallucination, safety, latency, and cost issues. • Fine-tune or adapt models where justified, using approaches such as supervised fine-tuning, LoRA , QLoRA , or PEFT, and document the trade-offs. • Integrate AI services with enterprise applications through Python services, REST APIs, event-driven patterns, and secure identity mechanisms.
• Deploy and operate solutions on Google Cloud using Vertex AI, Cloud Run or GKE, BigQuery , Cloud Storage, Pub/Sub, and related services. • Build CI/CD, testing, observability, release, rollback, and incident-response practices for AI applications. • Collaborate with solution architects, cloud engineers, technical engagement managers, customers, and distributed delivery teams. • Contribute reusable components, technical documentation, engineering standards, and mentoring for other engineers.
Essential Qualifications The recruitment profile requires a strong production engineering background together with practical Generative AI experience: • Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline. • At least 5 years of professional experience in software engineering, AI/ML engineering, data engineering, or a related technical field, including substantial delivery experience.
• Hands-on experience delivering AI or Generative AI solutions into production, not limited to experimentation or classroom projects. • Strong Python development skills, including API development with FastAPI , Flask, or comparable frameworks, plus testing and maintainable code practices. • Practical experience with LLMs, prompt engineering, RAG, embeddings, vector search, model evaluation, and agent or workflow patterns.
• Strong Google Cloud capability with Vertex AI and working knowledge of Gemini, BigQuery , Cloud Storage, Cloud Run or GKE, IAM, and monitoring.