QA Engineer, AI Products

MDCalc•,

2d•Remote

About The Position

Since 2005, MDCalc has been an essential part of the clinician’s workflow to help achieve better patient outcomes. Actively used by more than 65% of physicians worldwide, MDCalc is the most broadly used medical reference – at the point-of-care – for clinical decision tools and content, and one of only four references used by >50% of US HCPs. These evidence-based tools and content are used by millions of medical professionals globally and support 50+ specialties and cover 200+ patient conditions. To continue to further accelerate and steward this growth, we are expanding the AI product team with a QA Engineer. This role will be critical to MDCalc’s expanded success in continuing to support our millions of clinical users worldwide in taking care of hundreds of millions of patients.

Requirements

5+ years of experience in software QA, with at least 1 year of hands-on testing of LLM-based or AI/ML-powered features
Strong understanding of QA principles, test case creation/documentation, and best practices for both deterministic and non-deterministic systems
Hands-on experience with LLM tooling and concepts: prompt engineering, RAG systems, evaluation frameworks (e.g., Promptfoo, Braintrust, LangSmith, DeepEval, Ragas, OpenAI Evals), and LLM APIs (OpenAI, Anthropic, etc.)
Experience designing automated qualitative evaluation approaches, including LLM-as-judge, rubric-based scoring, semantic similarity checks, and golden dataset regression testing
Proficiency with test automation tools, with a focus on Playwright
Strong SQL skills for data validation, test data creation, and verifying data integrity across systems
Familiarity with token usage, latency profiling, and cost monitoring as quality signals
Eagerness to learn quickly and a positive, solutions-oriented attitude
Clear and concise communicator, able to surface issues, blockers, and risks effectively when communicating ambiguous or probabilistic failures
Self-motivated, proactive, and able to manage time and priorities independently

Responsibilities

Design and execute test strategies for LLM-powered features, including prompt regression testing, output evaluation, and hallucination detection
Build and maintain automated evaluation pipelines (eval sets, golden datasets, LLM-as-judge frameworks) to catch quality regressions in non-deterministic outputs
Perform black-box and exploratory testing of MDCalc's AI features across web and mobile, with particular attention to clinical accuracy, safety, and edge cases
Define quality metrics for AI outputs (accuracy, faithfulness, relevance, safety, latency, cost) and establish thresholds for release readiness
Collaborate cross-functionally with engineers, product managers, ML/AI engineers, and clinical reviewers to define what "good" looks like for AI responses
Investigate and triage AI failure modes, distinguishing model issues, prompt issues, retrieval issues, and integration bugs
Participate in team discussions, offering feedback on testability, risks, prompt design, and guardrails
Help develop QA strategies to expand future testing capacity, automation, and evaluation coverage as the AI product surface grows