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Job Title


AI ML Quality Engineering Leadership Role


Company : Zensar Technologies


Location : Chennai, Tamil Nadu


Created : 2026-01-26


Job Type : Full Time


Job Description

Greetings from Zensar!!We are looking for AI ML Test Quality engineering Leadership role.Experience: 15+ yearsLocation: Hyderabad/Bangalore/Pune/Chennai/KolkataWork Mode: Work from OfficeNotice period: Immediate JoinersJob description:- 15+ years of experience in Software Testing, Test Automation, and Quality Engineering, with at least 5+ years in a leadership role driving regional or global practices. - Strong BFS domain knowledge: core banking, payments, fraud detection. - Deep expertise in full-stack test automation: Web, API, Mobile/Digital, Database, and TDM solutions. - Strong exposure to AI/ML-based quality engineering practices – predictive analytics, autonomous AI for QE, self-healing automation, and intelligent test data management. - Experience in Multi-Agent Orchestration Systems across STLC, leveraging Agentic AI solutions, RAG (Retrieval-Augmented Generation), and LLMs for intelligent automation. - Ability to design and implement AI-driven workflows for user story refinement, test case generation, and automation script creation, ensuring measurable optimization and acceleration in QE processes. - Hands-on experience in setting up MCP (Model Context Protocol) servers to enable secure, scalable orchestration of AI agents across STLC phases, integrating context-aware prompts and multi-agent collaboration for QE automation. - Proven experience in technical consulting, solutioning, and assessments for large enterprise clients. - Strong background in pre-sales, RFPs, solution architecture, and business consulting. - Demonstrated ability to convert opportunities into revenue, aligning technical delivery with business outcomes. - Excellent client-facing, stakeholder management, and communication skills with the ability to influence CXO-level discussions. - Strong understanding of modern delivery models (Agile, DevOps, CI/CD, Cloud-native, Microservices). - Experience in building Center of Excellence (CoE) and driving knowledge sharing, accelerators, and IP creation.