Prototype to Spec: Instead of writing abstract requirements, you will build functional prototypes using tools like Streamlit, LangChain, or Python notebooks to validate feasibility. You verify prompt strategies in playgrounds (OpenAI, Anthropic, Vertex AI) before engineering writes a single line of production code.
Bridge the Technical Gap: Translate 'model constraints' (context windows, inference costs, probabilistic outputs) into concrete product mechanics. You will sit with engineers to debug edge cases, not just report them.
Own the 'Applied' in Applied AI: Drive the transition from 'model performance' (F1 scores) to 'product performance' (user success rates). You will define what 'good enough' looks like for production.
Wrangle Complex Data: Work hands-on with messy, real-world healthcare datasets (claims, EHR, patient-reported data). You view data quality not as someone else's problem, but as a core product asset.
Design for Trust, Speed & Explainability: Collaborate closely with Compliance, Design, and Engineering to build UIs that help users understand AI outputs, handle probabilistic edge cases gracefully, and foster user trust in the system. You also understand the critical tradeoffs between model accuracy and speed to insight, and design with this in mind.
Ship Responsibly: Design the guardrails, fallback mechanisms, and human-in-the-loop workflows that make AI safe and compliant in a healthcare setting.

Requirements

4–7 years of product experience, with at least 2+ years specifically building and shipping AI/ML products.
Strong preference for a CS background or previous experience as a software engineer/data scientist.
Working knowledge of the modern AI stack (LLMs, RAG architectures, vector databases, fine-tuning vs. context injection).
Ability to read technical documentation and understand API capabilities/limitations independently.
Experience navigating the complexity of healthcare data. You understand that 'patient safety' is the ultimate constraint.
You operate comfortably at every altitude. You can present a quarterly roadmap to executives, model the unit economics of AI features, and dive into the weeds to debug a prompt strategy—always balancing a 'magical user experience' against commercial viability and cost.
You are obsessed with closing the gap between model performance and real-world adoption, behavior change, and user/business impact.
You are comfortable working in a fast-paced dynamic environment and keeping many balls in the air, and are resourceful and willing to find creative ways to make a big impact quickly.

Benefits

Stock option plan
Flexible schedules and remote work
Chicago and San Francisco offices available
Self-managed vacation days, within reason
Paid parental leave
Health, vision, and dental insurance
401K retirement plan

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonAI/ML product developmentdata wranglingmodel performance evaluationF1 scoresAPI understandingfine-tuningcontext injectionvector databasesRAG architectures

Soft Skills

communicationproblem-solvingcollaborationadaptabilityresourcefulnesspresentation skillsuser experience focusdebuggingcritical thinkingproject management