Tata Consultancy Services
Gemini Enterprise AI Architect
Skills
23 days ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
4 October 2026
What they need
Role: Gemini Enterprise AI Architect
Experience: 8–10 Years
Location: Any
Employment Type: Full-time
We are seeking an experienced Gemini Enterprise AI Architect to design, architect, and deliver enterprise-scale Generative AI solutions leveraging Google Gemini, Vertex AI, Agentic AI frameworks, RAG architectures, and enterprise cloud platforms . The ideal candidate will drive AI transformation initiatives, define AI architecture standards, and lead the implementation of scalable, secure, and responsible AI solutions across business functions.
Key Responsibilities
- Design and architect end-to-end Gemini-powered AI solutions using Google Cloud Platform (GCP).
- Build enterprise-grade RAG (Retrieval Augmented Generation) and Agentic AI architectures.
- Implement AI applications using Gemini Models, Vertex AI, LangChain, LangGraph, Agent Development Kit (ADK), and Vector Databases .
- Define AI governance, security, compliance, and Responsible AI frameworks.
- Integrate AI solutions with enterprise applications, APIs, knowledge bases, and data platforms.
- Lead architecture reviews, performance optimization, and AI solution scalability initiatives.
- Mentor engineering teams and establish AI architecture best practices.
- Collaborate with business stakeholders to identify and prioritize GenAI use cases.
Required Skills
- 8–10 years of IT experience with at least 3+ years in Generative AI/LLM solutions .
- Strong expertise in Google Gemini Enterprise, Vertex AI, Model Garden, AI Studio, and GCP services .
- Hands-on experience with:
- RAG Architectures
- Agentic AI Systems
- Vector Databases (Pinecone, Weaviate, Vertex AI Vector Search, Chroma)
- LangChain / LangGraph
- Prompt Engineering and Evaluation Frameworks
- Strong programming expertise in Python .
- Experience with Cloud Architecture, API Integration, MLOps, CI/CD, Docker, Kubernetes .
- Knowledge of enterprise security, governance, and Responsible AI principles.
- Excellent stakeholder management and solution design skills.
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