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Senior R1 Rcm Medical Coding Jobs in Bronx, NY (NOW HIRING)

Commure

Senior Software Engineer, RCM Billing

New York, NY · Remote

$170K - $240K/yr

As a Senior Software Engineer Engineer, you will play a key role in scaling and maintaining our ... Conduct in-depth code reviews, uphold best practices, and drive architectural improvements across ...

Northwell Health

Coder

Lake Success, NY · On-site

$55K - $85K/yr

Make determinations on medical coding and takes initiative to complete reviews and coding ... Elevates questions, problems and significant challenges to more senior team members for direction ...

Akasa, Inc

Sr. Software Engineer, Backend

New York, NY · On-site +1

$120/hr

... are RCM startup of 2025 by Black Book Market Research, and one of the fastest-growing GenAI ... and Medical Coding suite. You will work closely with the product, design, and machine learning ...

Northwell Health

Coder

Lake Success, NY

$20 - $26.50/hr

Make determinations on medical coding and takes initiative to complete reviews and coding ... Elevates questions, problems and significant challenges to more senior team members for direction ...

Northwell

Coder

Lake Success, NY

$20 - $26.50/hr

Make determinations on medical coding and takes initiative to complete reviews and coding ... Elevates questions, problems and significant challenges to more senior team members for direction ...

Northwell

Coder

Lake Success, NY · On-site

$55K - $85K/yr

Make determinations on medical coding and takes initiative to complete reviews and coding ... Elevates questions, problems and significant challenges to more senior team members for direction ...

Northwell Health

Senior Coder

Lake Success, NY · Remote

$24.25 - $32.25/hr

Performs coding and abstracting duties to assure accurate completion of coding for all assigned patient records. Job Responsibility 1.Analyzes and interprets the medical record in its entirety to ...

Northwell Health

Senior Coder

Lake Success, NY · On-site

$66K - $108K/yr

Performs coding and abstracting duties to assure accurate completion of coding for all assigned patient records. Job Responsibility 1.Analyzes and interprets the medical record in its entirety to ...

Northwell

Senior Coder

Lake Success, NY · Remote

$66K - $108K/yr

Performs coding and abstracting duties to assure accurate completion of coding for all assigned patient records. Job Responsibility 1.Analyzes and interprets the medical record in its entirety to ...

Northwell

Senior Coder

Lake Success, NY · Remote

$24.25 - $32.25/hr

Performs coding and abstracting duties to assure accurate completion of coding for all assigned patient records. Job Responsibility 1.Analyzes and interprets the medical record in its entirety to ...

Palnar

Sr. Actimize Developer

Jersey City, NJ · On-site

$62.75 - $80/hr

... code and data analysis. * Software programming using SQL and Java, Python. * Knowledge of Database systems including Oracle and SQL Server * Working knowledge of Actimize. Expert in RCM Alerts/Case ...

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All JobsR1 Rcm Medical Coding JobsSenior R1 Rcm Medical Coding JobsSenior R1 Rcm Medical Coding Jobs in Bronx, NY

Senior R1 Rcm Medical Coding information

See Bronx, NY salary details

$16

$27

$39

How much do senior r1 rcm medical coding jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for senior r1 rcm medical coding in Bronx, NY is $27.46, according to ZipRecruiter salary data. Most workers in this role earn between $22.55 and $30.82 per hour, depending on experience, location, and employer.

What is the difference between Senior R1 Rcm Medical Coding vs Medical Coding Specialist?

AspectSenior R1 Rcm Medical CodingMedical Coding Specialist
CertificationsAHIMA/ACMEC certifications, CPC, CCSSimilar certifications, often CPC or CCS
Work EnvironmentHealthcare facilities, RCM companies, remote optionsHospitals, clinics, remote or onsite
Job ResponsibilitiesComplex coding, audits, mentoringStandard coding, claim submission
Experience LevelAdvanced, with years of experienceEntry to mid-level

Senior R1 Rcm Medical Coders typically handle complex cases, audits, and mentoring, requiring more experience and advanced certifications. Medical Coding Specialists focus on standard coding tasks and claim submissions, often at entry or mid-level. Both roles share similar certifications and work environments but differ in complexity and responsibility.

What are the most commonly searched types of R1 Rcm Medical Coding jobs in Bronx, NY? The most popular types of R1 Rcm Medical Coding jobs in Bronx, NY are:
What are popular job titles related to Senior R1 Rcm Medical Coding jobs in Bronx, NY? For Senior R1 Rcm Medical Coding jobs in Bronx, NY, the most frequently searched job titles are:
What cities near Bronx, NY are hiring for Senior R1 Rcm Medical Coding jobs? Cities near Bronx, NY with the most Senior R1 Rcm Medical Coding job openings:
Senior R1 Rcm Medical Coding jobs near you

Senior Applied AI Scientist, Clinical AI Agents

Phare Health

New York, NY • On-site, Remote

$140K - $300K/yr

Full-time

Medical, Retirement, PTO

Posted 7 days ago

Job description

About Us
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.
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.
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:
  • 180M+ Claims
  • 550M+ Patient encounters
  • 1.2B+ Workflow actions and outcomes each year

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.
The Role
  • We are looking for an Applied AI Engineer/Scientist to build, evaluate, and continuously improve clinical AI agents and supervised ML Models.
  • You will work at the intersection of software engineering, LLM systems, evaluation, model improvement, and deep healthcare workflow understanding. Your job is to turn frontier model capability into reliable production behavior: agents that read complex medical records, use the right clinical and coding context, call the right tools, produce auditable outputs, and improve from real-world failures.
  • You will be embedded in hard healthcare problems - clinical documentation integrity, medical coding, denial prevention, appeals, revenue cycle workflows, and payer logic - and will own the loop from problem framing to agent design, evaluation, deployment, trace analysis, and ongoing improvement.
  • The ideal candidate is a strong engineer who thinks like an applied scientist: rigorous about measurement, comfortable with ambiguity, excited by messy real-world data, and motivated by closing the gap between impressive demos and dependable production systems.

What You'll Do
  • 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 8+ 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
  • About Us
    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.
    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.
    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:
    • 180M+ Claims
    • 550M+ Patient encounters
    • 1.2B+ Workflow actions and outcomes each year

    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.
    The Role
    • We are looking for an Applied AI Engineer/Scientist to build, evaluate, and continuously improve clinical AI agents and supervised ML Models.
    • You will work at the intersection of software engineering, LLM systems, evaluation, model improvement, and deep healthcare workflow understanding. Your job is to turn frontier model capability into reliable production behavior: agents that read complex medical records, use the right clinical and coding context, call the right tools, produce auditable outputs, and improve from real-world failures.
    • You will be embedded in hard healthcare problems - clinical documentation integrity, medical coding, denial prevention, appeals, revenue cycle workflows, and payer logic - and will own the loop from problem framing to agent design, evaluation, deployment, trace analysis, and ongoing improvement.
    • The ideal candidate is a strong engineer who thinks like an applied scientist: rigorous about measurement, comfortable with ambiguity, excited by messy real-world data, and motivated by closing the gap between impressive demos and dependable production systems.

    What You'll Do
    • 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
    • Senior: Team Lead responsible for managing a portfolio of projects that contribute to major technical initiatives.
    • 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.

    Benefits
    • Top-of-market compensation (salary + equity)
    • Flexible PTO
    • Comprehensive health benefits
    • 401(k) matching
    • Inspiring, brilliant, mission-driven teammates

    Hiring Flow
    • Intro call - your background & our mission alignment
    • 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)
    • References
    • Offer

    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, nat

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