Gen Ai QA Engineer

Contact: Asif Raza Contact Email: asifraza@hanstaffing.com Contact Phone: (551) 795-0621

Company: HAN Staffing Tests AI model outputs and application functionality. Validates data accuracy, business logic and system performance. - Design and execute test plans covering AI model outputs, data correctness, and application functionality. Create automated tests for APIs and UI where appropriate; maintain regression suites. Validate business logic, edge cases, and non-functional requirements (performance, reliability).Establish evaluation criteria for AI components (accuracy, hallucination checks, guardrail adherence).Triage defects, document reproducible steps, and partner with engineers to resolve issues. Contribute to release readiness, quality gates, and continuous improvement of testing practices. AI-driven Agentic Software Engineer (Fullstack)

Rate: - 60-70/Hr on C2CLocation: Onsite (Hartford, CT, OR Minneapolis, MN) locals preferred.

Client: Virtusa / Health Care CompanyJD:-Build full-stack applications that integrate AI/ML outputs into user-facing and backend workflows. Develop APIs and services that orchestrate model inference, prompt flows, and agent/tool integrations. Leverage AI coding assistants (e.g., Git Hub Copilot, agentic IDEs) to accelerate delivery while maintaining quality. Implement UI/UX experiences for AI-enabled features (explanations, feedback loops, human-in-the-loop controls).Apply secure SDLC practices: code reviews, testing, dependency management, and vulnerability remediation. Partner with architects and platform teams to align to standards and reuse shared components.5+ years building production software (backend and/or frontend) in Java/Python/.NET ecosystems. Experience with web frameworks and modern UI (React or similar) and REST API development. Working knowledge of CI/CD, Git workflows, and automated testing. Comfort integrating with ML services, LLM/agent runtimes, or data platforms via APIs. Strong problem-solving skills and ability to deliver iteratively in an agile environment. Experience building internal tools or copilots with prompt engineering and tool/function calling. Experience with observability for AI features (quality metrics, prompt/model versioning).UX experience designing AI interactions and feedback capture. Fullstack Integration, LLM Orchestration, and User Experience. Mandatory Skills (The "Must-Haves")LLM Orchestration: Mastery of frameworks like Lang Chain or Lang Graph to manage multi-turn agentic workflows. GenAI Implementation: Practical experience with RAG (Retrieval-Augmented Generation) using vector databases like FAISS, Pinecone, or Azure Cognitive Search. API & Microservices: Advanced development of services that orchestrate model inference and tool integrations using FastAPI or Node.js. AI Coding Assistants: Effective use of Git Hub Copilot or agentic IDEs to accelerate delivery without sacrificing code quality. UI/UX for AI: Ability to build "human-in-the-loop" controls and feedback loops into the frontend. Good-to-Have Skills Vector Embeddings: Deep understanding of embedding models (e.g., OpenAI Ada) and chunking strategies. Containerization: Proficiency in Docker and Kubernetes (AKS/EKS) for sustaining high throughput (1K+ RPS).Observability: Experience with Open Telemetry or Azure Monitor to track agent reliability and response accuracy.