Agentic AI / GenAI Engineer

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 environment.

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.