Applied AI Engineer

R1 RCM

. Design, build, and iterate on agentic AI systems for complex healthcare workflows, including documentation, coding, denial management, appeals, and revenue cycle automation .

Posted 10/8/2026full-timeRemote • United StatesMid-LevelSenior💰 $140,000 - $270,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building agentic AI systems for healthcare workflows, with strong proficiency in Python and experience in developing evaluation frameworks and performance monitoring for AI systems.

Highest-signal resume keywords

Python ProficiencyAI Systems DevelopmentEvaluation Framework DesignMachine Learning EngineeringProduction Application Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringMachine Learning EngineeringApplied AIAPIsTestingLoggingObservabilityLLM ApplicationsPrompt EngineeringPerformance Monitoring

Soft Skills

CollaborationProblem-SolvingAdaptability

Tools & Technologies

Experiment TrackingBenchmarkingReproducible EvaluationAI Infrastructure

Industry Keywords

Healthcare WorkflowsRevenue Cycle AutomationDenial ManagementHuman-in-the-Loop ReviewContext Construction

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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 specifications, rubrics, gold standards, test cases, and clinically meaningful success criteria for clinical agents
Build evaluation and feedback loops using expert review, production logs, model outputs, and benchmarks
Measure performance, regressions, edge cases, safety, reliability, provenance quality, and business impact
Prototype AI capabilities and harden them into reliable, explainable, auditable production systems
Partner with research and ML engineering teams on model selection, fine-tuning, reward modeling, distillation, synthetic data, post-training, and internal AI infrastructure
Work with instrumentation, experiment tracking, benchmarking, prompt/version management, and reproducible evaluation
Collaborate with clinical, product, and engineering teams to translate real-world healthcare challenges into scalable AI systems

Requirements

What you’ll need

4+ years of experience in software engineering, machine learning engineering, applied AI, research engineering, or a related field
Strong proficiency in Python
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

Benefits

Comp & perks

Top-of-market compensation, including bonus that starts at 10%
Flexible PTO
Comprehensive health benefits
401(k) matching
Inspiring, brilliant, mission-driven teammates
Annual bonus plan at a target of 10.00%
Opportunities to constantly learn, collaborate across groups and explore new paths for your career
Competitive benefits package