Tata Consultancy Services · Pune
Sr AI Engineer
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 →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.</p
Qualifications
BACHELOR OF TECHNOLOGY
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AI Engineer
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