Senior Agentic AI Architect – Enterprise AI Ecosystem

Job description

**Senior Agentic AI Architect – Enterprise AI Ecosystem** **Greetings from TCS!** ! **!** **Walk in Drive planned on 4th July 2026 in TCS Kochi.** TCS has been a great pioneer in feeding the fire of young Techies like you. We are a global leader in the technology arena and there’s nothing that can stop us from growing together. Your role is of key importance, as it lays down the foundation for the entire project. Make sure you have a valid EP number before interview. To create an EP Number, please visit https://ibegin.tcs.com/iBegin/register Kindly complete the registration if you have not done it yet. Position: **Senior Agentic AI Architect – Enterprise AI Ecosystem** Exp **erience: 15 to 20 years** L **ocation: Kochi** **JOB DESCRIPTIO** N **Role: Senior Agentic AI Architect – Enterprise AI Ecosystem** **Required Information** **Details** 1 **Role\\*** Senior Agentic AI Architect – Enterprise AI Ecosystem **2 Required Technical Skill Name\\*** Generative AI, Agentic AI, Enterprise AI Architecture, Multi-Agent Orchestration, RAG, Knowledge Graphs, Vector Databases, Python, LangChain / LangGraph / CrewAI, Cloud, Microservices, Event-Driven Architecture **4 Desired Experience Range\\*** 15–20 Years **5 Location of Requirement \\*** Kochi, India **Desired Competencies (Technical/Behavioral Competency)** **Must-Have** **1. Enterprise AI Architecture Design** - Define and implement end-to-end agentic AI architecture - Design scalable frameworks for multi-agent orchestration - Build knowledge-driven architectures using knowledge graphs and contextual intelligence - Enable enterprise-wide AI ecosystem integration across business functions **2. Agentic System Engineering (Hands-on)** - Design and build autonomous AI agents capable of planning, reasoning, and tool usage - Develop multi-agent workflows and orchestration frameworks - Implement RAG (Retrieval-Augmented Generation) and knowledge-based reasoning - Create reusable agent frameworks and components **3. AI Ecosystem & Platform Engineering** - Build and scale enterprise AI platforms and knowledge systems - Design and manage data pipelines (structured and unstructured) - Integrate enterprise applications, APIs, and backend systems - Architect layered AI ecosystems (Data, Knowledge, Intelligence, and Work layers) **4. Governance, Security & Responsible AI** - Implement AI governance frameworks, guardrails, and compliance controls - Ensure privacy-by-design, PII protection, and regulatory adherence - Enable audit logging, explainability, and observability - Embed security across AI workflows and data lifecycle **5. Scalability & Performance Engineering** - Design systems for high scalability, concurrency, and reliability - Optimize token usage, latency, and infrastructure cost - Implement CI/CD pipelines for AI model and agent deployment - Enable distributed execution of agent workflows **6. Enterprise AI Transformation** - Drive transition from AI-as-tool to AI-as-operating-model - Redesign business processes for autonomous decision-making - Enable human-AI collaboration at scale - Lead enterprise AI adoption and transformation initiatives **7. Stakeholder Leadership & Governance** - Collaborate with business, platform, data, and security teams - Define AI strategy, roadmap, and architecture standards - Lead cross-functional AI programs and large-scale implementations - Provide architectural guidance to engineering teams **Required Skills & Expertise** **Core Technical Skills** - Strong experience in Generative AI and Agentic AI systems - Hands-on experience with frameworks like LangChain, LangGraph, CrewAI - Proficiency in Python - Experience with Vector DBs, Knowledge Graphs, and enterprise data systems - Cloud expertise (Azure / AWS / GCP) - Strong understanding of microservices and event-driven architecture **Responsibility / Expectations** 1 Define and implement **end-to-end Agentic AI architecture** for enterprise-scale ecosystems. 2 Design scalable frameworks for **multi-agent orchestration** and enterprise AI ecosystem integration across business functions. 3 Build **knowledge-driven architectures** using knowledge graphs, contextual intelligence, RAG, vector databases, and enterprise data sources. 4 Design and build autonomous AI agents capable of **planning, reasoning, and tool usage** . 5 Develop **multi-agent workflows, orchestration frameworks, reusable agent frameworks, and reusable AI components** . 6 Implement **RAG and knowledge-based reasoning** patterns for enterprise AI solutions. 7 Build and scale **enterprise AI platforms and knowledge systems** . 8 Design and manage data pipelines for **structured and unstructured data** . 9 Integrate enterprise applications, APIs, backend systems, and architect layered AI ecosystems covering **Data, Knowledge, Intelligence, and Work layers** . 10 Implement **AI governance frameworks, guardrails, compliance controls, privacy-by-design, PII protection, regulatory adherence, audit logging, explainability, and observability** . 11 Embed security across **AI workflows and data lifecycle** . 12 Design systems for **high scalability, concurrency, reliability, low latency, token optimization, infrastructure cost optimization, and distributed execution** . 13 Implement **CI/CD pipelines for AI model and agent deployment** . 14 Drive transition from **AI-as-tool to AI-as-operating-model** . 15 Redesign business processes for **autonomous decision-making** and enable **human-AI collaboration at scale** . 16 Lead enterprise AI adoption and transformation initiatives. 17 Collaborate with **business, platform, data, and security teams** to define AI strategy, roadmap, and architecture standards. 18 Lead cross-functional AI programs, large-scale implementations, and provide architectural guidance to engineering teams. **Also please refer below link for downloading application form. 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