Tcs Hiring For Gemini Enterprise & Agentic AI Solution Architect

Job description

**TCS Hiring for Gemini Enterprise & Agentic AI Solution Architect** Role: Agentic AI Solution Architect Location: Pan India Experience: 10 - 15 Years **Education:** - Minimum 15 years of regular,full-time education (10 + 2 + 3) (B. Tech preferred) - Google Cloud certifications (Professional Cloud Architect, ML Engineer) **Job Role** We are hiring an experienced Solution Architect Agentic AI to design and deliver enterprise-scale intelligent agent solutions using Google Cloud’s Gemini Enterprise, Vertex AI, and Agent Development Kit (ADK). This role focuses on building agentic AI systems capable of reasoning, planning, collaboration, and autonomous execution across enterprise applications. Google’s ecosystem enables multimodal AI solutions with Gemini models, orchestration through Vertex AI, ADK-driven agent development, secure integrations, contextual memory, and enterprise-grade scalability. **Skills:** - 8–12+ years in solution architecture, cloud engineering, or AI/ML - Strong expertise in GCP (Vertex AI, Cloud Run, IAM, Pub/Sub, Workflows) - Experience with LLM-based applications and AI agents - Hands-on experience with Gemini or similar models - Proficiency in Python and APIs - Experience with agent frameworks (LangChain, LangGraph, AutoGen, CrewAI) - Knowledge of RAG architectures and vector databases - Understanding of distributed systems and microservices - Hands-on experience with Gemini Enterprise and Vertex AI Agent Builder - Experience designing multi-agent systems - Familiarity with MCP and agent communication protocols - Knowledge of Responsible AI frameworkst - Strong solution architecture and design skills - Ability to translate business requirements into AI solutions - Expertise in scalable and secure AI deployments - Understanding of agentic AI patterns (reasoning, orchestration) - Strong communication and stakeholder management skills **Responsibilities:** - Lead architecture and implementation of agentic AI solutions using Gemini Enterprise and Vertex AI - Design single-agent and multi-agent systems for enterprise automation and copilots - Develop intelligent agents using Agent Development Kit (ADK) - Integrate agents with enterprise applications using APIs, Pub/Sub, and microservices - Leverage Cloud Functions, Cloud Run, and Workflows for execution and orchestration - Implement memory-driven agents with short-term and long-term context handling (RAG) - Design secure tool usage frameworks with governance controls - Build scalable CI/CD pipelines and MLOps-based deployments - Enable observability using Cloud Logging, Monitoring, and evaluation frameworks - Mentor teams and define best practices for agent lifecycle management