Lab, R1 RCM - Applied AI Scientist, Clinical AI Agents
Requirements
• Technical deep-dives - pseudo-coding exercise and systems design (not Leetcode) • Final in-person interview at one of our hubs (SF, NYC, Austin, or Chicago; travel arranged) • Interview Logistics Notice • As part of our hiring process, selected candidates will participate in an in-person interview. Candidates located near one of our talent hubs—San Francisco, New York, Austin, or Chicago—will be scheduled to meet with team members in those locations. For candidates residing outside these areas, we will arrange travel to a hub for the interview. Travel accommodation will be provided as needed. We are committed to providing equal employment opportunities and ensuring a fair and inclusive experience for all applicants. • For this US-based position, the base pay range is $140,000.00-$300,000 per year. Individual pay is determined by role, level, location, job-related skills, experience, and relevant education or training. • This job is eligible to participate in our annual bonus plan. • The healthcare system is always evolving — and it’s up to us to use our shared expertise to find new solutions that can keep up. On our growing team you’ll find the opportunity to constantly learn, collaborate across groups, and explore new paths for your career. • Our associates are given the chance to contribute, think boldly, and create meaningful work that makes a difference in the communities we serve around the world. We go beyond expectations in everything we do. Not only does that drive customer success and improve patient care, but that same enthusiasm is applied to giving back to the community and taking care of our team — including offering a competitive benefits package. • R1 RCM Inc. (“the Company”) is dedicated to the fundamentals of equal employment opportunity. The Company’s employment practices , including those regarding recruitment, hiring, assignment, promotion, compensation, benefits, training, discipline, and termination shall not be based on any person’s age, color, national origin, citizenship status, physical or mental disability, medical condition, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status or any other characteristic protected by federal, state or local law. Furthermore, the Company is dedicated to providing a workplace free from harassment based on any of the foregoing protected categories. • If you have a disability and require a reasonable accommodation to complete any part of the job application process, please contact us at 312-496-7709 for assistance. • CA PRIVACY NOTICE: California resident job applicants can learn more about their privacy rights California Consent • CA PRIVACY NOTICE: • For applicants outside of California: Please review our policy - R1 Non-Disclosure Consent • For applicants outside of California: • To learn more, visit: R1RCM.com • Visit us on Facebook • CA PRIVACY NOTICE:
Responsibilities
• Design, build, and iterate on agentic AI systems for complex healthcare workflows, including documentation, coding, denial management, appeals, and revenue cycle automation. • Develop long-horizon agent behavior across context construction, retrieval, tool use, memory, routing, verification, escalation, and human-in-the-loop review. • Define what “good” looks like for clinical agents end-to-end, translating expert workflows into specifications, rubrics, gold standards, test cases, and clinically meaningful success criteria. • Build rigorous evaluation and feedback loops using expert review, production logs, model outputs, and benchmarks to measure performance, regressions, edge cases, safety, reliability, provenance quality, and business impact. • Prototype new AI capabilities from 0 → 1, then harden them into reliable, explainable, auditable production systems with clear contracts, monitoring, evidence, rationale, and performance gates. • Partner with research and ML engineering teams on model selection, fine-tuning, reward modeling, distillation, synthetic data, post-training, and internal AI infrastructure, including instrumentation, experiment tracking, benchmarking, prompt/version management, and reproducible evaluation. • What Makes This Role Different • Most AI roles are either too research-heavy or too product-light. This role sits in the middle. • You will not only write prompts or run experiments. You will own whether an agent actually works in production. That means understanding the workflow, designing the system, building the evals, inspecting failures, improving the agent, and proving that the improvement matters. • The right person will be excited by questions like: • What context does this agent need to make the right decision? • How do we know the output is clinically and operationally correct? • Which failures are prompt problems, retrieval problems, model problems, tool problems, or product-spec problems? • How do we turn expert feedback into a better benchmark or training set? • When should we use prompting, RAG, rules, fine-tuning, reward modeling, or a different architecture? • How do we make agent outputs auditable enough for clinical and operational review? • How do we build a data flywheel that improves the system every week? • You May Be a Good Fit If You • Bring 4+ years of software engineering, ML engineering, research engineering, or applied AI experience. • Are highly proficient in Python and comfortable building production systems with APIs, structured data, async workflows, testing, logging, and observability. • Have experience turning messy real-world workflows into structured AI problems, including classification, ranking, extraction, decisioning, LLM applications, agents, RAG, tool calling, structured outputs, prompting, or evaluation. • Have built or operated evaluation systems, benchmarks, annotation workflows, experiment tracking, or regression tests for AI systems. • Thrive in ambiguous, high-stakes domains: working with experts, debugging real-world failures, and turning model potential into reliable, correct, safe systems that work for users. • Role Leveling • We are looking for candidates at various levels, ranging from Level 2 to Staff • L2: Independently delivers a complete end-to-end project, owning design, implementation, and delivery of scoped work • L3: Leads delivery of larger projects, handling increased technical complexity and ambiguity, providing light guidance to L2s on shared work
Benefits
• Phare Health is now part of R1 and its AI innovation engine, R37 Lab, bringing Phare’s frontier clinical reasoning technology together with one of the largest healthcare platforms in the U.S. • R37 Lab • At R37 and Phare, we are building the first AI-native Healthcare Revenue Operating System: a connected platform that reasons over full medical records, payer logic, and financial workflows to automate medical coding, billing, and follow-up. • first AI-native Healthcare Revenue Operating System • Backed by real customers, real data, and real distribution, we operate on a national scale. Our agentic AI systems already power production workflows across 95 of the top 100 U.S. health systems, processing hundreds of millions of patient encounters each year, including: • 95 of the top 100 U.S. health systems • 180M+ • 550M+ Patient encounters • 550M+ • 1.2B+ Workflow actions and outcomes each year • 1.2B+ • This is startup-level ownership with enterprise-level impact. If you want to build AI that ships, scales, and measurably improves how healthcare works, this is the place to do it. • Top-of-market compensation (salary + equity) • 401(k) matching • Inspiring, brilliant, mission-driven teammates • Hiring Flow
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT