Staff Software Engineer, AI

Onos Health

. Develop LLM/NLU systems to process and extract meaningful information from clinical notes and medical documents .

Posted 10/1/2026full-timeSan Francisco • California • United StatesLead💰 $200,000 - $275,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying LLM/NLU systems for processing clinical notes and medical documents, with a strong focus on data privacy, security, and healthcare compliance. Proven ability to build scalable data pipelines and integrate AI/ML capabilities into existing platforms while ensuring adherence to industry standards.

Highest-signal resume keywords

LLM/NLU System DevelopmentData Pipeline EngineeringHealthcare Data CompliancePython ProgrammingAWS Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM-Based SystemsData EngineeringMachine LearningPythonDjangoPostgreSQLDockerMLOps Best PracticesBenchmarking FrameworksModel Governance

Soft Skills

Collaborative Team PlayerCustomer ObsessedResults-Oriented

Tools & Technologies

AWS (ECS, Bedrock, Cognito)GitHub ActionsCeleryDjango-ninjaDjango-tenantsS3JiraCodeRabbitAITuskClaude

Industry Keywords

Healthcare DataHIPAA Best PracticesClinical AssessmentsBehavioral HealthLevel-of-Care Guidelines

Tech Stack

Tools & technologies

AWSDjangoDockerPostgresPython

About the role

Key responsibilities & impact

Develop LLM/NLU systems to process and extract meaningful information from clinical notes and medical documents
Classify patients according to level-of-care guidelines and make accurate recommendations
Establish best practices for LLM/AI systems, benchmarking/evaluation frameworks, and model governance
Build scalable data pipelines while maintaining strict data privacy and security standards
Collaborate with backend engineers to integrate AI/ML capabilities into the Onos platform
Build and operationalize AI/data pipelines for analyzing medical records and streamlining clinical assessments and healthcare quality reviews
Benchmark LLM systems to extract evidence from medical records and classify patients’ level-of-care recommendations
Develop and optimize systems that ingest medical standards-of-care documents and evaluate provider adherence to guidelines
Design explainable AI solutions that provide transparency into model decisions for healthcare professionals
Take ownership of a significant part of the Onos platform while working as an early team member across backend and data engineering responsibilities

Requirements

What you’ll need

5+ years experience building and deploying applications in production in a backend engineering / data engineering capacity
Relevant experience with developing LLM-based systems for ingesting and evaluating unstructured records for industry-specific use cases and integrating them with user-facing features
Deep understanding of the limitations of using LLMs and the best practices for using them for reliable, consistent, and accurate outputs
Customer obsessed and motivated to build a best-in-class model for behavioral health clinical assessments in the healthcare space
A collaborative team player with a focus on delivering measurable results
Specifically worked with medical records to evaluate whether a patient’s history meets criteria for evaluations or assessments (e.g., claims authorization or other types of evaluations)
Experience wearing multiple hats as a generalist backend engineer
Experience working with data pipelines and Python and related data science/ML libraries
Significant experience working with healthcare data and with HIPAA best practices
Knowledge of modern LLM and ML infrastructure and MLOps best practices
AWS (ECS, Bedrock, Cognito, etc.)
Docker
GitHub Actions
Python, Django, Celery, django-ninja, django-tenants
PostgreSQL (AWS RDS)
S3
GitHub, Jira, CodeRabbitAI, Tusk, Claude

Benefits

Comp & perks

Flexible hybrid arrangement: 2-3 days/week at San Francisco office (Financial District), remote-first culture
Unlimited vacation policy
Paid parental leave
Medical, dental, and vision insurance
Pre-tax commuter benefits
401(k)
Significant equity as an early employee
Direct mentorship from experienced founders
Ground-floor opportunity to help build a team and culture
Regular team events and offsites
Company-provided equipment and home office setup