Greeting from TCS

We are looking for

Role: Agentic AI / GenAI Engineer

Required Technical Skill -Strong experience in designing, developing, integrating, testing, and

deploying enterprise software solutions with expertise in Agentic AI,

Machine Learning-enabled applications, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), tool-calling and multi-agent

orchestration frameworks. Hands-on experience with Python

development, API integration, data engineering, semantic retrieval,

context and prompt management, intent classification, recommendation

systems, workflow automation, Jira integration, secure software

development, model evaluation, telemetry, observability, CI/CD pipelines, BDD/Gherkin-based automation, and end-to-end software lifecycle delivery.

Desired Experience Range: 4-8 years

Location of Requirement: India

Must-Have

- Hands-on experience building ML-enabled, Agentic AI, or GenAI software using Python and API-driven service patterns.
- Strong experience implementing LLM-based workflows, retrieval-augmented generation, secure context assembly, response grounding, and source traceability.
- Experience developing tool-calling agents, multi-step workflows, human-review gates, deterministic rules, guardrails, exception handling, and safe fallback behavior.
- Experience implementing natural-language interactions, intent classification, confidence thresholds, missing-information detection, clarification prompts, and workflow routing.
- Ability to build structured and unstructured retrieval services, semantic search, similarity matching, recommendations, prioritization, and next-best-action capabilities.
- Experience integrating enterprise systems through approved APIs for data retrieval, status lookup,



record creation or update, report generation, notifications, and workflow initiation.
- Knowledge of data ingestion, normalization, canonical models, enrichment, entity resolution, data-quality indicators, lineage, and cross-system traceability.
- Experience with secure software development, role-based access, least privilege, audit logging, prompt/tool governance, secrets handling, and confidential-data protection.
- Experience developing automated unit and integration tests, model or recommendation evaluations, telemetry, logging, CI/CD pipelines, and repository traceability.
- Strong analytical, troubleshooting, documentation, communication, and collaborative delivery skills in an agile engineering setting.

Good-to-Have

- Automotive Verification and Validation, test-management, release-planning, bench-scheduling, or defect-management domain exposure.
- Experience with Jira integration, defect-signal analysis, evidence summarization, duplicate detection, defect-quality scoring, and lifecycle tracking.
- Experience building planning recommendations, test-case prioritization, bench matching, scheduling, optimization, conflict detection, and explainability workflows.
- Knowledge of vector retrieval, search engineering, decision intelligence, event/change detection, risk scoring, readiness assessment, or knowledge graphs.
- Familiarity with BDD, Gherkin, requirements documentation, acceptance checklists, demonstration evidence, and employee handover artifacts.
- Experience integrating reporting and dashboards for usage, workflow outcomes, model performance, automation effectiveness, and operational telemetry.
- Ability to work with distributed product, data, API, security, QA, ML-governance, and domain-specialist teams.

📌 Agentic AI / GenAI Engineer (India)
🏢 Tata Consultancy Services
📍 India