Staff Software Engineer, Applied AI

About this role

Parachute Health is transforming post-acute care as the leading digital ordering platform for medical equipment and supplies. We connect major health systems, health plans, and suppliers to help patients get the life-saving products they need at home. Since launching, we've connected 300,000+ clinicians and 3,000+ supplier locations across all 50 states and helped 15M+ patients. What started as a DME ePrescribing tool has become the order management platform of choice for home medical equipment.

Join our team and make a difference in patient care.

About the Team

We're an incubator-style team inside Parachute Health, scaling AI capabilities across the entire product ecosystem.

What you'll do

• Design and build agentic LLM pipelines that power AI features across the product.

• Build full-stack product features: Python/FastAPI web applications, TypeScript or React web tooling.

• Prompt-engineer and iterate on LLM prompts and models. Evaluate and recommend improvements based on accuracy, latency, and cost.

• Strengthen our evaluation framework: curated datasets, evals, experiments, and regression identification, so we can ship changes with confidence.

• Improve production observability: accuracy signals and feedback loops.

• Contribute to architecture and technical direction.

• Actively partner with other product teams to understand their AI use cases and identify how to best enable and support them.

• Advise on when to apply an AI/LLM solution, and when not to: championing AI where it drives speed and ROI and steering away where it doesn't.

Requirements

• 5+ years of professional software engineering experience

• Experience working in a startup, incubator, or other fast-paced 0-to-1 environment where you own features end-to-end and set your own direction.

• Strong full-stack web application experience in Python.

• Has shipped reliable agentic LLM workflows to production, with any orchestration framework (LangGraph, LangChain, etc).

• Experience evaluating and testing LLM workflows: eval harnesses, golden datasets, regressions, and observability.

• Familiarity with prompt engineering and the prompt iteration lifecycle.

• Fluent with AI-powered coding tools (e.g. Cursor, Claude Code) to move quickly.

• Strong written and verbal communication; able to drive alignment without being asked.

• Must reside in the U.S.

Nice to Have

• Healthcare workflows or health-tech experience.

• Ruby on Rails experience

• A track record of evaluating emerging AI tools and driving their adoption on a team.

Benefits

• Medical, Dental, and Vision Coverage: Comprehensive plans with options for low-to-no-cost premiums.

• Employer HSA…