Quality Assurance Architect

• 10–14 years as a Technology Architect, SDET, or QE Leader with strong coding skills in Python, Type Script, or Java.
• Proven experience designing automation frameworks or developer tools for large engineering organizations.
• Hands‑on expertise with Large Language Models (LLMs), prompt engineering, and safety evaluation techniques.
• Exposure to Agentic AI systems and orchestration tools such as Lang Graph, Auto Gen, CrewAI, or similar agent frameworks.
• Experience implementing Model Context Protocol (MCP) for real‑time automation, autonomous workflows, or CI/CD integrations.
• Experience working in highly regulated industries—Energy, Utilities, Nuclear, Healthcare, BFSI, or similar.

AI / ML Technologies

• Practical experience with frameworks and ecosystems:
• Working knowledge of ML/DL libraries:

Scikit-learn, Tensor Flow, Keras, PyTorch, Hugging Face Transformers, OpenCV, NLTK and BART

• Understanding of RAG architectures, embeddings, and semantic search (bonus).

GenAI & AI Agent Development

• Expertise in designing, developing, validating, and deploying Generative AI solutions.
• Experience building AI agents, multi‑agent workflows, or autonomous decision systems.
• Ability to define governance for:

• Agent monitoring & observability
• Automated evaluation gates
• Continuous monitoring & drift alerts

Automation & Quality Engineering

• Strong experience building test automation frameworks using Python, PyTest, Selenium, Playwright, and Requests.
• Ability to create automated tests covering:

• Functional
• API
• Integration
• Performance
• Security

AI Governance & Compliance

• Establish AI/ML quality standards, testing guidelines, and risk controls.
• Define governance around:

• Data security & privacy
• Regulatory alignment for Energy/Utility operations
• Continuous monitoring & drift alerts

Cloud, Dev Ops & CI/CD

• Knowledge of deploying AI and automation solutions on AWS.
• Experience implementing CI/CD pipelines for ML and LLM models:

• Automated evaluation gates

• Experience implementing observability frameworks for AI/ML systems.
• Strong understanding of end‑to‑end SDLC and QE methodologies.
• Work closely with developers, product managers, data scientists, and business stakeholders.
• Ability to provide clear communication around test strategy, risks, coverage, and governance readiness.

Skilled in defect triage, risk‑based testing, and quality strategy leadership