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AI ML Quality Engineering Leadership

Job in 600001, Chennai, Tamil Nadu, India
Listing for: Zensar Technologies
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    AI Engineer, Cloud Computing
Job Description & How to Apply Below
Position: AI ML Quality Engineering Leadership Role
Greetings from Zensar!!

We are looking for AI ML Test Quality engineering Leadership role.

Experience:

15+ years

Location:

Hyderabad/Bangalore/Pune/Chennai/Kolkata

Work Mode:
Work from Office

Notice period:
Immediate Joiners

Job 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, Dev Ops, CI/CD, Cloud-native, Microservices).
- Experience in building Center of Excellence (CoE) and driving knowledge sharing, accelerators, and IP creation.
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