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Onos Health
Onos Health
11 – 50 Employees
Artificial IntelligenceHealthcareHealthcare Insurance
Onos Health develops AI-powered clinical intelligence for behavioral health payers. Its platform turns unstructured clinical records, including session notes, treatment plans, and assessments, into insights that support clinical quality, utilization management, program integrity, and provider network management. The company’s solutions address behavioral health across care levels such as ABA, substance use disorder treatment, mild-to-moderate mental health, and serious mental illness, spanning inpatient, residential, PHP/IOP, and outpatient settings. Onos Health combines payer-focused implementation, enterprise security, and responsible AI practices, with a team operating at the intersection of healthcare, health insurance, and artificial intelligence.
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Staff AI Software Engineer at Onos Health

Lead AI engineering for Onos Health’s healthcare data platform by building LLM systems, clinical assessment models, scalable pipelines, and explainable recommendations.

USUnited StatesCACalifornia
$200,000 – $275,000 / year
HybridFull-timeLeadEnglish RequiredAI EngineerMachine Learning Engineer
AWSDjangoDockerPostgresPython

Description

  • Create LLM and natural language understanding systems that process and extract insights from clinical notes and medical documents
  • Classify patients against level-of-care guidelines and produce accurate recommendations
  • Define engineering practices for LLM and AI systems, evaluation and benchmarking frameworks, and model governance
  • Develop scalable data pipelines that uphold rigorous privacy and security requirements
  • Partner with backend engineers to integrate AI and machine learning capabilities into the Onos platform
  • Build and operate AI and data pipelines that analyze medical records and improve clinical assessments and healthcare quality reviews
  • Evaluate LLM performance in extracting evidence from medical records and assigning level-of-care recommendations
  • Develop and refine systems that ingest medical standards-of-care documents and assess provider adherence to guidelines
  • Create explainable AI solutions that clarify model decisions for healthcare professionals
  • Own a substantial area of the Onos platform while contributing across backend and data engineering as an early team member

Requirements

  • At least five years of experience building and deploying production applications in backend or data engineering roles
  • Experience developing LLM-based systems that ingest and evaluate unstructured, industry-specific records and connect to user-facing features
  • Strong understanding of LLM limitations and techniques for producing reliable, consistent, and accurate outputs
  • Customer-focused mindset with motivation to build a high-quality behavioral health clinical assessment model
  • Collaborative approach with an emphasis on delivering measurable outcomes
  • Hands-on experience using medical records to determine whether patient histories satisfy evaluation or assessment criteria, such as claims authorization
  • Background as a generalist backend engineer who can work across multiple responsibilities
  • Experience building data pipelines with Python and related data science or machine learning libraries
  • Substantial experience handling healthcare data and applying HIPAA best practices
  • Knowledge of current LLM and machine learning infrastructure and MLOps practices
  • Experience with AWS services including ECS, Bedrock, and Cognito
  • Experience using Docker
  • Experience with GitHub Actions
  • Experience with Python, Django, Celery, django-ninja, and django-tenants
  • Experience with PostgreSQL on AWS RDS and S3
  • Familiarity with GitHub, Jira, CodeRabbitAI, Tusk, and Claude
  • ],

Benefits

  • Flexible hybrid schedule with two to three days per week in the San Francisco Financial District office and a remote-first culture
  • Unlimited vacation
  • Paid parental leave
  • Medical, dental, and vision insurance
  • Pre-tax commuter benefits
  • 401(k) plan
  • Meaningful equity for an early employee
  • Direct mentorship from experienced founders
  • Opportunity to help shape the team and company culture from an early stage
  • Regular team events and offsites
  • Company-provided equipment and home office setup

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