[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Tata Consultancy Services jobs](https://jobs.opennash.com/companies/tata-consultancy-services/) · [Search jobs](/search/) Tata Consultancy Services · Pune # Sr AI Engineer Pune Senior individual contributor Operations Last seen on Tata Consultancy Services’s official careers site on August 1, 2026; it may have closed since. [Apply on Tata Consultancy Services’s careers site →](https://ibegin.tcsapps.com/candidate/next/en-IN/jobs/425175J) [OpenNash Jobs](https://jobs.opennash.com/) / [Tata Consultancy Services](https://jobs.opennash.com/companies/tata-consultancy-services/) / Sr AI Engineer ## Job description - Build & Ship GenAI / Agentic Features - Develop and deploy RAG pipelines, agent workflows, copilots, and AI-powered microservices on Azure, AWS or GCP — typically across more than one cloud per engagement. - Implement chunking, embedding, indexing, hybrid retrieval and re-ranking strategies tuned to banking corpora (policy documents, regulatory text, contracts, customer correspondence, code, structured data). - Design and implement tool-use, function-calling and structured-output patterns; orchestrate multi-step agents with planning, reflection, memory and human-in-the-loop checkpoints. - Integrate with banking systems of record (core banking, CRM, ECM/document repositories, fraud platforms, ticketing systems) via secure APIs and event streams. - Quality, Evaluation & Safety - Build and maintain golden datasets and evaluation harnesses; instrument pipelines with metrics for groundedness, faithf ulness, latency-per-token, cost-per-call and user-feedback signals. - Implement guardrails — input filtering, output validation, schema enforcement, PII redaction, prompt-injection defenses and jailbreak detection. - Participate in red-teaming exercises and remediate findings; contribute to model cards and decision logs for audit and MRM reviews. - MLOps / LLMOps & Reliability - Containerize services, write infrastructure-as-code, and ship through CI/CD pipelines including evaluation gates for prompts, chains and agents. - Set up observability for AI systems — distributed tracing, prompt/response logging (with redaction), token-level cost dashboards, and alerting on quality regressions. - Own production support for your services on a rotating basis; conduct blameless post-mortems and drive permanent fixes. - Collaboration & Continuous Learning - Partner with product managers, designers and banking SMEs to shape requirements and demonstrate progress through frequent, working increments. - Contribute to internal accelerators, reusable components, and the AI engineering knowledge base; mentor junior engineers and interns. - Stay current with the rapidly evolving GenAI/Agentic ecosystem — models, frameworks, evaluation techniques, and security patterns — and bring relevant innovations into the practice.