QA / AI Evaluation Engineer

Who you are

• We are looking for people who can bring a strong, solution-focused mindset and contribute to quality standards, best practices and get things done
• Bachelor’s Degree in a technical field or equivalent experience
• 4+ years in QA / test engineering, with exposure to data/ML systems
• Strong Python and data-science techniques for measuring factual grounding and answer quality
• Experience with LLM evaluation frameworks and statistical analysis
• Ability to build automated, large-scale eval harnesses plus lighter human-in-the-loop A/B tests
• Comfort working across multiple LLM providers’ outputs
• Test automation frameworks and scripting
• Detail-oriented, with strong analytical and communication skills
• You think about how to scale, automate and operate, not just how to build a solution to an immediate problem
• You understand lean thinking
• You set high standards for code quality, performance/scalability and security and seek continuous improvement
• You have solid analytical, problem solving and decision-making skills
• You have customer first mindset and a devotion to customer service
• You engage and build positive internal and external client relationships, while managing multiple initiatives, often with competing priorities
• You have strong self-initiative, passion, interpersonal, oral and written communication and collaboration skills with the ability to work, influence and make an impact in a cross-functional environment with all levels of the organization
• You are responsive and thrive in a fast-paced diverse high-performance environment with rapidly changing business needs
• You actively seek out things outside your comfort zone with the ability to rapidly learn and take advantage of new concepts, business models, and technologies
• You have prior experience in consulting
• Prior experience and connections in the Life Sciences industry is preferred

What the job involves

• As a QA / AI Evaluation Engineer, you will join a highly motivated and experienced team in a forward-leaning role that proves the platform actually improves answer quality. You will run evaluations at scale — from small human-UAT batches up to millions of automated evals — statistically measure factual grounding and accuracy lift, and build the metrics framework that shows how much better our answers get over time
• Run evals at scale across large question sets, from small human-UAT batches up to hundreds of thousands or millions of automated evaluations
• Statistically measure factual grounding and accuracy lift (before/after), not just human A/B testing
• Build a metrics framework showing quality improvement (e.g., “answer is X% supported by source content / Y% better”)
• Design load and quality tests as the corpus scales
• Define and maintain test plans, test cases, and quality gates
• Automate regression and evaluation suites; integrate them into CI/CD
• Report quality metrics clearly to technical and non-technical stakeholders
• Collaborate with engineering to reproduce, triage, and verify fixes
• Continuously improve QA processes and coverage