Gen AI Engineer
Tata Consultancy Services
6 - 10 years
Kochi
Posted: 23/04/2026
Job Description
Job description
Greetings from TCS!
Job Title: Gen AI Engineer
Walkin Interview Date: 25th April 26
Walkin Location: Infopark Road Infopark Campus, Infopark E, Kakkanad, Kerala 682045
Walkin Time: 9am-1pm
Experience Range: 6-10 yrs
Job description:
TCS has always been in the spotlight for being adept in the next big technologies. What we can offer you is a space to explore varied technologies and quench your techie soul.
What we are looking for:
Role Summary
Experienced Generative AI (GenAI) Engineer with 6-10 years of software/ML engineering experience and a strong track record of delivering LLM-powered applications into production. The role involves designing and building GenAI solutions such as RAG-based assistants, copilots, agent workflows, and enterprise knowledge systems, ensuring they are secure, scalable, observable, and cost-efficient. The engineer will work closely with product, data, security, and platform teams to create measurable business outcomes while establishing best practices for LLMOps, evaluation, and responsible AI.
Key Responsibilities
- Build and productionize LLM-powered applications (chatbots, copilots, summarization, search/Q&A, document intelligence) with measurable quality and reliability.
- Design and implement Retrieval-Augmented Generation (RAG) solutions: chunking strategies, embeddings, hybrid search, ranking, prompt templates, grounding, and citation-based responses.
- Develop agentic workflows: tool/function calling, multi-step reasoning pipelines, orchestration, retry/fallback logic, and state management for complex tasks.
- Implement LLMOps practices: prompt/version control, evaluation pipelines, model routing, A/B testing, cost monitoring, and automated regression testing.
- Create scalable inference services and APIs (REST/gRPC) with performance optimization (latency, throughput, caching, streaming responses).
- Build and maintain vector and knowledge layers: indexing pipelines, metadata enrichment, access control filtering, freshness strategies, and re-index automation.
- Implement guardrails and safety controls: input/output filtering, jailbreak detection patterns, PII redaction, policy-based access, content moderation, and audit logging.
- Establish observability and monitoring: quality metrics, grounding metrics, hallucination rate, drift, token usage, latency, error rates, and user feedback loops.
- Collaborate with security/compliance to ensure enterprise requirements (RBAC, encryption, data residency, retention, DLP) are built into the solution.
- Mentor junior engineers and contribute reusable components, internal libraries, templates, and reference architectures.
Minimum Qualification: 15 years of full-time education
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