> Markdown version of [/jobs/ext/4467165-applied-ai-scientist](https://www.wearedevelopers.com/jobs/ext/4467165-applied-ai-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Applied AI Scientist

- **Company:** R1 RCM Inc.
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $140,000.0 - $270,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Python (Programming Language), Machine Learning, Software Engineering, AI Infrastructure, Data Logging, Retrieval-Augmented Generation, Large Language Models, Grafana, Prompt Engineering, Agentic-AI, Performance Monitor, Machine Learning Operations, Software Version Control
- **Published:** October 9, 2026
- **Apply:** https://www.builtincolorado.com/job/applied-ai-engineer-r37/11586019?handler=ApplyRedirect

## About the Role

* 4+ years of experience in software engineering, machine learning engineering, applied AI, research engineering, or a related field.

 * Strong proficiency in Python and experience building production applications using APIs, structured data, testing, logging, and observability tools.

 * Experience with LLM applications, AI agents, RAG (Retrieval-Augmented Generation), prompt engineering, tool calling, structured outputs, or machine learning systems.

 * Experience designing evaluation frameworks, benchmarks, experimentation workflows, and performance monitoring for AI systems.

 * Ability to work in ambiguous, high-impact environments and translate complex real-world problems into scalable AI solutions.

## Description

Our flagship platform, Phare OS, uses AI and automation to improve critical pre-bill workflows, including authorization, utilization management, documentation and coding. By identifying and resolving issues before claims are submitted, Phare OS helps prevent denials, improve reimbursement and move revenue cycle work upstream.

What makes R37 different is the opportunity to build advanced AI at real-world scale. R1 works across 95 of the top 100 U.S. health systems, giving R37 access to the data, workflows and reach needed to make an immediate impact:

 * 180M+ claims

 * 550M+ patient encounters

 * 1.2B+ workflow actions and outcomes annually

This is startup-level ownership with enterprise-level impact. You'll build technology that moves from idea to real healthcare environments, solving complex problems at scale and changing how healthcare works.

As our Applied AI Scientist, you will help transform complex healthcare workflows into reliable, production-ready AI solutions that improve clinical and revenue cycle outcomes. Every day you will design and optimize AI agents for healthcare use cases, evaluate and improve model performance through rigorous testing and feedback loops, and collaborate with clinical, product, and engineering teams to translate real-world challenges into scalable AI systems.

To thrive in this role, you must be highly proficient in Python, passionate about building dependable AI systems, comfortable navigating ambiguity, and excited about solving complex healthcare problems using agentic AI, machine learning, and LLM technologies.

Here's what you will experience working as an Applied AI Scientist:

 * 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., 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 (Compensation Range for L2: $140k - $200k)

 * L3: Leads delivery of larger projects, handling increased technical complexity and ambiguity, providing light guidance to L2s on shared work (Compensation Range for L3: $140k - $253k)

 * Senior: Team Lead responsible for managing a portfolio of projects that contribute to major technical initiatives. (Compensation Range for Senior: $140k - $294k)

 * Staff: Impact at the organizational level. Responsible for leading multiple teams or multiple broad initiatives simultaneously, ensuring that high-level technical goals are met across the entire organization. (Compensation Range for Staff: $140k - $350k)