QA Automation Engineer - GenAI / LLM Testing (Healthcare)

Project description

Join Our Team: Innovating Health Care with Cutting-Edge Technology We are looking for an experienced AI Quality Engineer to design and implement quality engineering strategies for AI-enabled applications, platforms, and services. The role focuses on automated testing, AI model evaluation, and ensuring the accuracy, reliability, safety, and compliance of Generative AI, LLM, and machine learning solutions within enterprise environments.

Responsibilities

• Design and execute comprehensive testing strategies for AI/ML, GenAI, LLM, and intelligent automation solutions. Develop and maintain automated testing frameworks covering functional, non-functional, and AI-specific requirements. Evaluate AI-generated outputs for accuracy, reliability, consistency, bias, fairness, safety, and Responsible AI compliance. Collaborate with engineering, product, data science, and business teams to identify quality risks and establish acceptance criteria. Produce quality metrics, testing documentation, governance evidence, and recommendations supporting AI deployment and production monitoring.

SKILLS

Must have

• - Quality Engineering
  - Test Automation
  - AI / ML Testing
  - Generative AI / LLM Testing
  - Python / Java
  - API Testing
  - Integration Testing
  - Data Validation
  - Responsible AI
  - AI Model Evaluation
  - Test Framework Development
  - CI/CD
  - Agile / SDLC
  
  Mandatory Skills Description 3–5+ years of experience in Quality Engineering, Quality Assurance, or Software Testing, including 3+ years in test automation development and 2+ years testing AI, machine learning, Generative AI, LLM, or intelligent automation solutions. Strong experience designing automated test frameworks, validating AI-generated outputs, and performing API, integration, and data testing. Proficiency in Python, Java, or similar programming languages, with solid knowledge of Agile, SDLC, CI/CD, and Responsible AI principles, including fairness, bias detection, transparency, explainability, and human oversight. Strong analytical, communication, and cross-functional collaboration skills are required.
  
  Experience testing RAG pipelines, chatbots, conversational AI, AI agents, and LLM-based applications, including hallucination detection, prompt robustness, model drift, bias, and adversarial testing. Knowledge of AI evaluation frameworks, test harnesses, MLOps, AI governance, and cloud platforms such as Azure, AWS, or GCP. Experience within healthcare, payer, provider, pharmacy, claims, or other regulated environments is preferred. Familiarity with accessibility testing, audit and compliance processes, and mentoring QA engineers is a plus.
  
  AI Tool Expectations: Consistent use of enterprise-approved AI tools, including GitHub Copilot and Microsoft 365 Copilot, targeting a minimum of 90% weekly utilization to enhance testing, documentation, analysis, and delivery efficiency.

Nice to have

Exceptional communication skills. Ability to deliver exceptional customer service with a positive attitude.

Remote United States, United States of America