Senior Software Engineer (AI)

What you'll be doing at Onos

• 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
• Own and evolve our LLM evaluation harness, regression gates, and observability to ensure our systems catch accuracy regressions before they reach payers and prove the platform's reliability over time
• Extract structured data from visually complex clinical documents, including scanned charts, tables, and graphs using a mix of OCR, multimodal models, and classical ML
• Collaborate with backend engineers to integrate AI/ML capabilities seamlessly into the Onos platform

Technical Challenges

• Build and operationalize AI/data pipelines to analyze medical records to streamline clinical assessments and healthcare quality reviews
• Benchmark and stress-test LLM systems so evidence extraction and level-of-care classification stay accurate and reliable as criteria, documents, and models change
• Develop and optimize a system that ingests complex medical standards of care documents and evaluates provider adherence to guidelines
• Design explainable AI solutions that provide transparency into model decisions for healthcare professionals

Tech Stack

• Infrastructure/Systems: AWS (ECS, Bedrock, Cognito, etc.), Docker, Github Actions
• Languages/Frameworks: Python, Django, Celery, django-ninja, django-tenants
• Database/Storage: PostgreSQL (AWS RDS), S3
• Development Tools: Github, Jira, CoderabbitAI, Tusk, Claude

What we're looking for

• 4+ 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
• Experience with document AI, OCR, or extracting data from visual/scanned content (charts, graphs, tables)
• 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 best-in-class models for behavioral health clinical assessments in the healthcare space
• A collaborative team player with a focus on delivering measurable results

Bonus points if you have

• 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

Benefits and 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