AI Engineer - Evaluations
About The Position
As an AI Engineer - Evaluations at Hippocratic AI, you'll define and build the systems that measure, validate, and improve the intelligence, safety, and empathy of our voice-based generative healthcare agents. Evaluation sits at the heart of our model improvement loop - it informs architecture choices, training priorities, and launch decisions for every patient-facing agent. You'll design LLM-based auto-evaluators, agent harnesses, and feedback pipelines that ensure each model interaction is clinically safe, contextually aware, and grounded in healthcare best practices. You'll collaborate closely with research, product, and clinical teams, working across the stack - from backend data pipelines and evaluation frameworks to tooling that surfaces insights for model iteration. Your work will directly shape how our agents behave, accelerating both their reliability and their real-world impact.
Requirements
- 3+ years of software or ML engineering experience with a track record of shipping production systems end-to-end.
- Proficiency in Python and experience building data pipelines, evaluation frameworks, or ML infrastructure.
- Familiarity with LLM evaluation techniques - including prompt testing, multi-agent workflows, and tool-using systems.
- Understanding of deep learning fundamentals and how offline datasets, evaluation data, and experiments drive model reliability.
- Excellent communication skills with the ability to partner effectively across engineering, research, and clinical domains.
- Passion for safety, quality, and real-world impact in AI-driven healthcare products.
Nice To Haves
- Experience developing agent harnesses or simulation environments for model testing.
- Background in AI safety, healthcare QA, or human feedback evaluation (RLHF).
- Familiarity with reinforcement learning, retrieval-augmented evaluation, or long-context model testing.
Responsibilities
- Design and build evaluation frameworks and harnesses that measure the performance, safety, and trustworthiness of Hippocratic AI's generative voice agents.
- Prototype and deploy LLM-based evaluators to assess reasoning quality, empathy, factual correctness, and adherence to clinical safety standards.
- Build feedback pipelines that connect evaluation signals directly to model improvement and retraining loops.
- Partner with AI researchers and product teams to turn qualitative gaps into clear, defensible, and reproducible metrics.
- Develop reusable systems and tooling that enable contributions from across the company, steadily raising the quality bar for model behavior and user experience.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
101-250 employees
