Job Summary
We are seeking an AI QE Architect to lead the design, development, and optimization of next-generation AI-powered quality engineering solutions and platforms. This role combines deep technical expertise in automation engineering with hands-on experience in LLMs, agentic AI frameworks, and enterprise-grade AI tooling. The architect will define strategy, design scalable frameworks, guide teams, and drive innovation across QE automation, AI agents, RAG pipelines, and MCP-enabled intelligent workflows.

Key Responsibilities
• Design, develop, and optimize AI-powered quality engineering solutions and scalable automation platforms.
• Apply hands-on experience with LLMs, prompt engineering, RAG, vector databases, and model evaluation.
• Develop and enhance GenAI-powered QE solutions, AI agents, and autonomous workflows.
• Implement MCP-driven, context-aware automation and CI/CD decision intelligence.
• Design and maintain automation frameworks for UI, API, and performance testing.
• Develop prompt-optimized, AI-generated test assets and validation mechanisms.
• Build data and embedding pipelines and optimize retrieval capabilities for RAG solutions.
• Implement CI/CD processes for ML models, including versioning, evaluation, and retraining workflows.
• Integrate automation pipelines using GitHub Actions, Azure DevOps, Jenkins, and related tools.
• Ensure AI and automation environments are scalable, secure, and governed.
• Provide technical leadership and mentor teams on AI adoption and automation engineering best practices.
• Collaborate with developers, SMEs, and product teams to align architecture and technology roadmaps.
• Drive feature prioritization, quality strategy, and solution design.
• Lead defect triage, quality reviews, and compliance with QE and AI governance requirements.
• Contribute across the full SDLC, including test strategy, design, execution, and analysis.
• Operate effectively within Agile/Scrum development environments.

Required Qualifications
• Strong hands-on experience with LLMs, prompt engineering, RAG, vector databases, and model evaluation.
• Proficiency with LangChain, HuggingFace, Transformers, and OpenAI/Ollama APIs.
• Experience with agentic AI frameworks such as LangGraph, AutoGen, or CrewAI.
• Strong programming skills in Python, TypeScript, or Java.
• Experience architecting and maintaining automation frameworks.
• Hands-on experience with UI automation tools such as Playwright and Selenium.
• Experience with API testing tools and frameworks such as PyTest, Requests, and RestAssured.
• Experience with performance testing tools such as JMeter and Locust.
• Experience with PyTorch, TensorFlow, Scikit-Learn, and NLP/CV libraries such as NLTK, BART, or OpenCV.
• Experience building data and embedding pipelines and optimizing retrieval for RAG.
• Strong understanding of AWS, Azure, or GCP architectures and AI/ML services.
• Experience integrating automation and CI/CD pipelines using GitHub Actions, Azure DevOps, Jenkins, or similar tools.
• Strong understanding of scalable, secure, and governed AI and automation environments.
• Experience working across the full SDLC in an Agile/Scrum environment.

Preferred Qualifications
• Experience designing enterprise-grade AI-powered quality engineering platforms.
• Experience with MCP-enabled intelligent workflows and context-aware automation.
• Experience implementing AI-generated testing assets and automated validation mechanisms.
• Experience with ML model versioning, evaluation, and retraining workflows.
• Experience providing technical leadership and mentoring engineering teams.
• Experience driving AI adoption, QE strategy, and automation innovation across enterprise environments.