AI_QE_Architect

Experience:

Key Skills & Responsibilities

• Strong hands-on experience with LLMs, prompt engineering, RAG, vector DBs, and model evaluation.
• Proficiency with LangChain, HuggingFace, Transformers, OpenAI/Ollama APIs.
• Experience to agentic AI frameworks like LangGraph, AutoGen, CrewAI.
• Build and enhance GenAI-powered QE solutions, AI agents, and autonomous workflows.
• Implement MCP-driven, context-aware automation and CI/CD decision intelligence.

Automation Engineering

• Strong coding skills in Python, TypeScript, or Java.
• Architect and maintain automation frameworks for:
• UI: Playwright, Selenium
• API: PyTest, Requests, RestAssured
• Performance: JMeter, Locust
• Develop prompt-optimized, AI-generated test assets and validation mechanisms.

ML/AI Engineering & Data Pipelines

• Experience with PyTorch, TensorFlow, Scikit-Learn, NLP/CV libraries (NLTK, BART, OpenCV).
• Build data/embedding pipelines and optimize retrieval for RAG.
• Implement CI/CD for ML models, including versioning, evaluation, and retraining workflows.

Cloud, DevOps & Integration

• Strong understanding of AWS/Azure/GCP architectures and AI/ML services.
• Integrate automation pipelines using GitHub Actions, Azure DevOps, Jenkins.
• Ensure scalable, secure, and governed AI/automation environments.

Leadership & Delivery Excellence

• Provide technical leadership and mentor teams on AI adoption and automation best practices.
• Collaborate closely with developers, SMEs, and product teams to align on architecture and roadmap.
• Drive feature prioritization, quality strategy, and solution design.
• Lead defect triage, quality reviews, and compliance with QE/AI governance.
• Work across the full SDLC, contributing to test strategy, design, execution, and analysis.
• Operate effectively in an Agile/Scrum environment.