Quality Assurance Architect

Base Pay Range

$/yr - $/yr

• 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.

• 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)

• 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

• Strong experience building test automation frameworks using Python, PyTest, Selenium, Playwright, and Requests
• Ability to create automated tests covering:
  • Functional
  • API
  • Integration
  • Performance
  • Security
• Proficiency in API testing and validation of RESTful services
• Plus:
  Experience with performance/load testing tools K6 or JMeter

• 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
• Experience working with IRB, compliance, or audit teams

• 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

Mid‑Senior level

Full‑time

Quality Assurance and Engineering

IT Services and IT Consulting, Financial Services, and Investment Banking

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