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. 

• Experience with containers, CI/CD, version control, secure software delivery, and LLMOps or MLOps practices. 

• Ability to diagnose production issues and balance quality, reliability, latency, security, and cost. 

• Professional English communication skills and experience collaborating with international or customer-facing teams. 

Preferred Qualifications 

• Experience with Google Agent Development Kit, LangChain, LangGraph, Semantic Kernel, or comparable frameworks. 

• Experience with fine-tuning libraries such as PEFT, TRL, or Hugging Face Transformers. 

• Google Cloud Professional Machine Learning Engineer, Professional Data Engineer, or equivalent certification. 

• Experience with responsible AI, red teaming, privacy, security controls, and enterprise data governance. 

• English language proficiency or experience supporting APAC-based stakeholders. 

Success Measures 

• AI services are delivered on schedule and meet agreed quality, security, availability, latency, and cost targets. 

• RAG, agent, and model-evaluation workflows produce measurable improvements in answer quality and user outcomes. 

• Production incidents are diagnosed and resolved with clear root-cause analysis and preventive actions. 

• Reusable engineering assets and documentation accelerate subsequent Google Engineer business engagements. 

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.