AI Quality Engineering Lead

Job description

We are seeking an AI Quality Engineering Lead  with 8+ years of experience in Quality Engineering, Test Automation, Software Engineering, and AI/ML. The role will lead the design and adoption of AI-powered Quality Engineering solutions, automation frameworks, and Agentic AI capabilities across the SDLC.

Roles and Responsibilities

Lead AI-powered Quality Engineering and Test Automation initiatives.

Design and implement Agentic AI, LLM, RAG, and Multi-Agent  solutions.

Build reusable AI frameworks, accelerators, agents, libraries, and reference architectures.

Develop AI solutions for test generation, automation, defect analysis, traceability, test data, documentation, and quality analytics.

Establish AI governance, Responsible AI, security, observability, model evaluation, and Human-in-the-Loop  practices.

Integrate AI solutions with DevOps, CI/CD, and cloud-native platforms .

Provide technical leadership, mentoring, architecture guidance, and stakeholder management.

Required Skills

8+ years  in Quality Engineering, Software Engineering, Test Automation, AI/ML, or technology delivery.

3+ years  designing and implementing AI/ML, GenAI, or Agentic AI solutions.

Strong Python, FastAPI, LangChain, LangGraph, LLMs, RAG, and Prompt Engineering  experience.

Experience with Multi-Agent Systems, Microservices, API-first/Event-Driven Architecture .

Hands-on experience with Docker, Kubernetes, DevOps, and CI/CD .

Experience in AI/ML solution architecture, enterprise frameworks, and engineering transformation.

Knowledge of AI governance, Responsible AI, security, observability, and model evaluation.

Strong technical leadership and communication skills.

Experience with Azure AI, OpenAI, and Azure AI Search  is preferred.

Education

Bachelor’s degree or higher in Computer Science, Engineering, AI/ML, Data Science, or a related field.

Who can apply

Review the original listing for work authorization, qualifications and employer requirements.