Applied AI Engineer for Healthcare Revenue & Coding

RiseMe

South San Francisco (CA)

On-site

USD 180,000 - 250,000

Full time

2 days ago
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Benefits offered by this job

Flexible PTO
Health/Dental/Vision coverage
HSA contributions
Parental leave
Life insurance
Home office stipend
Phone/internet reimbursement
Company holidays
401(K)

Job summary

AKASA seeks an Applied AI Engineer to build AI-powered solutions across our Clinical Documentation and Medical Coding suite. You will partner with product, design, and ML teams to design services, APIs, and tools for our SaaS products.

You will contribute to AI-native products that improve physician documentation, identify missing diagnoses, and ensure financial integrity for health systems, impacting thousands of clinicians nationwide.

Qualifications

  • Bachelor of Science in Computer Science or related field.
  • 3+ years in a technical role with AI/data analysis or backend systems.
  • 1+ years shipping production AI systems to end users.
  • Experience designing offline/online evaluations and landing agentic systems.
  • Proficiency in Python.
  • Thrives in a startup environment working on challenging problems.
  • Healthcare technology experience (EDI, HL7, FHIR) is a plus.

Responsibilities

  • Build features and products driven by LLMs across the stack.
  • Collaborate with product, clinical, and revenue cycle experts on complex problems.
  • Deploy evaluation frameworks and experimentation loops for production-grade systems.
  • Work with product, design, and ML teams to design and build services and APIs.

Skills

Python
AI development
Data analysis
Production systems
Startups
Healthcare tech

Education

BS in Computer Science

Job description

AKASA seeks an Applied AI Engineer to build AI-powered solutions across our Clinical Documentation and Medical Coding suite. You will partner with product, design, and ML teams to design services, APIs, and tools for our SaaS products.

You will contribute to AI-native products that improve physician documentation, identify missing diagnoses, and ensure financial integrity for health systems, impacting thousands of clinicians nationwide.

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