AI QE Architect
apexonBethesda (MD)
About the role
AI QE Architect _ Bethesda, MD The AI QE Architect will lead the design, development, and optimization of next-generation AI-powered quality engineering solutions, including 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 Skills & ResponsibilitiesAI, LLMs & Agentic Systems Strong hands-on experience with LLMs, prompt engineering, RAG, vector DBs, and model evaluation. Proficiency with Lang Chain, Hugging Face, Transformers, OpenAI/Ollama APIs. Experience to agentic AI frameworks like Lang Graph, Auto Gen, 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, Type Script, or Java. Architect and maintain automation frameworks for:oUI: Playwright, SeleniumoAPI: PyTest, Requests, Rest Assuredo Performance: JMeter, Locust Develop prompt-optimized, AI-generated test assets and validation mechanisms. ML/AI Engineering & Data Pipelines Experience with PyTorch, Tensor Flow, 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, Dev Ops & Integration Strong understanding of AWS/Azure/GCP architectures and AI/ML services. Integrate automation pipelines using Git Hub Actions, Azure Dev Ops, 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.
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