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Senior R1 Rcm Medical Coding Jobs in Concord, CA

Senior Medical Planner

San Francisco, CA Β· On-site

$130K - $160K/yr

The Senior Medical Planner is an integral part of the design team and will lead the planning and ... codes and agency processes. * Responsible for coordinating team members and consultants ...

Admitting Worker Senior

San Francisco, CA Β· On-site

$108K - $137K/yr

The Senior Admitting Worker must comply with all guidelines put forth by the Medical Center ... Responsible for appropriately responding to emergency situations including but not limited to code ...

... RCM processing billions in claims, all on a single AI-native platform integrated with 60+ EHRs ... Establish best practices for code quality, testing, deployment, and observability * Mentor ...

Showing results 21-40

Senior R1 Rcm Medical Coding information

See Concord, CA salary details

$16

$28

$41

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

As of Sep 13, 2026, the average hourly pay for senior r1 rcm medical coding in Concord, CA is $28.92, according to ZipRecruiter salary data. Most workers in this role earn between $23.75 and $32.45 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 popular job titles related to Senior R1 Rcm Medical Coding jobs in Concord, CA?

For Senior R1 Rcm Medical Coding jobs in Concord, CA, the most frequently searched job titles are:

What cities near Concord, CA are hiring for Senior R1 Rcm Medical Coding jobs?

Cities near Concord, CA with the most Senior R1 Rcm Medical Coding job openings:

Infographic showing various Senior R1 Rcm Medical Coding job openings in Concord, CA as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $60,151 per year, or $28.9 per hour.

Senior Forward Deployed AI Engineer / Solutions Architect (GenAI, AWS)

San Francisco, CA β€’ On-site

$65 - $84/hr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 19 days ago


Job description

About the role:

Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete.

Our work centers on two verticals - Financial Services & Insurance and Healthcare & Life Sciences - where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.

We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) - people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints.

You will do the customer's job before you automate it.

Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it.

A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagementΒ in the operator's seatΒ - as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we've been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive andΒ rebuild the function from first principlesΒ - and you are the one who builds it.

Three things define how you work:

- Embedded, not engaged. You are part of the customer's team and inside their process - not a vendor running a project alongside it.

- Real tasks, not scope. You are not fenced into a siloed deliverable. You go where the operating problem is.

- Autonomous. Embedded is not staff-augmented. You own the method; nobody hands you a ticket.

You won't start from zero. Provectus buildsΒ industry blueprintsΒ - working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice.

You'll be measured on whether the Business Unit's number moved - not on hours, not on scope delivered.

This is a role for engineers who have led before - as a founder, a CTO, a staff engineer - and who want to stay in the code while owning the outcome. On most days you'll be the most senior technical person in the room, and you'll still be the one shipping.

What you'll do:
  • 8+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way.
  • You will take the operator's seat.Β You are genuinely willing to spend weeks doing someone else's job - claims processing, underwriting, revenue-cycle work - before you write a line of code. Engineers who need to stay in the IDE should not apply.
  • You learn domains fast.Β Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living.
  • Shipped GenAI/LLM systems to productionΒ - not demos, not notebooks. You've handled the parts that get hard after the prototype works.
  • You evaluate.Β You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why.
  • Strong engineering fundamentalsΒ - dropped into an unfamiliar codebase or language, you're productive. Python and/or TypeScript proficiency; depth matters more than stack.
  • Cloud-native delivery on AWSΒ (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits.
  • Credible with senior stakeholdersΒ - you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room.
  • Comfort with ambiguity and ownership.Β Engagements start underspecified by design. Closing that gap is the job.
  • Solid AI/ML foundations - you understand what the models do well enough to reason about failure modes, not just call the API.
  • Strong hands-on prodcution experience with Claude Code/Cowork.
  • Fluent English, written and spoken.
Nice to have:
  • Prior experience as aΒ founder, CTO, or engineering leaderΒ who has chosen to return to individual contribution.
  • Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management.
  • Consulting, professional services, or other embedded customer-facing delivery.
  • Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality.
  • MLOps and classical ML: PyTorch, SageMaker, MLflow.
  • Fine-tuning, distillation, or inference/serving optimization.
  • Graph databases (Neo4j, AWS Neptune).
  • IaC depth: AWS CDK, CloudFormation, Terraform.
  • Open-source contributions or public writing on applied AI.
What We Offer:
  • Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare
  • The chance to shape how leading enterprises adopt AI, from strategy through first deployment
  • A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
  • A growing AI delivery practice where you help build the tooling and frameworks, not just use them
  • Remote-friendly culture
  • High-impact role with direct visibility to leadership
  • Strong earning potential with performance-based bonuses
  • Opportunity to work with cutting-edge AI and cloud solutions
  • Unlimited Vacation policy
  • Generous health, vision, and dental insurance
  • 401(K) matching plan
  • OTE range $150-180k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data.
How we hire:

Short loop, hands-on, no take-home:

  1. Intro conversationΒ - the role, your background, what you want to be doing.
  2. Two live engineering sessions.Β Real problems, your own editor.Β You may use an LLM assistantΒ (ChatGPT, Claude) - how you work now includes these tools.Β Autocomplete/agentic coding tools are offΒ for these sessions.
  3. The redesign session.Β We hand you an unfamiliar business function and the constraints of the person who performs it. You have to understand the job well enough to rebuild it - then say what you'd build and how you'd know it worked. No LLMs for this one.
  4. Team and practice conversation.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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