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# Staff Software Engineer

- **Company:** Develop Health Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Debugging, Design of User Interfaces, Operational Data Store, Software Architecture, Software Engineering, Systems Integration, Backend
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/staff-software-engineer-san-francisco-ca--732a8393-e3f3-46d3-a718-6554a468dbe1

## About the Role

Software Engineering, Healthcare, Medications, Artificial Intelligence (AI), Pharmacy, Startup, Funding, Compensation and Benefits, Canvas, Software Engineering, * Experience building AI-powered or automation-heavy products in production.

 * Experience with healthcare, clinical workflows, EHRs, payers, pharmacies, or another regulated domain.
 * Early-stage startup experience or evidence that you thrive with high ownership and limited structure.
 * Experience building workflow products, data-heavy interfaces, or third-party integrations.

## Description

Were hiring a Staff Software Engineer to turn complex healthcare problems into simple, reliable software. This is a hands-on role with ownership from understanding user needs through launch and production.

Together with Product, AI, and Operations, youll build the systems that remove the obstacles between a prescription and treatment, from the interfaces people use to the services, integrations, and AI-powered workflows behind them.

Youll raise the bar for the engineering team through the technical decisions you make and the AI-native tools and practices you share.

What Youll Do - Impact In Your First 3-6 Months

 * Work with users to turn an ambiguous problem into the smallest useful solution and a clear measure of success.
 * Lead a complex product initiative from discovery through launch, defining the technical approach and milestones while personally building the critical parts.
 * Ship across backend services, user interfaces, data models, integrations, and workflow infrastructure.
 * Make architectural decisions across systems and explain the trade-offs clearly, so what we ship today still fits where the product is going.
 * Build testing, observability, safe rollouts, and AI fallbacks into the product, then iterate using production evidence and user feedback.

What Youll Own - Beyond 6 Months

 * Own the technical direction and customer outcomes of major product areas.
 * Solve technical problems that span products, and build shared services that make the next product faster to ship and run.
 * Shape the roadmap using customer evidence and operational data.
 * Build AI-native tools and engineering processes that help the whole team work with agents at every stage of development (planning, implementation, review, testing, and production).

What Youll Bring On Day One

 * Hands-on engineering. You have 5+ years of software engineering experience and can build, debug, and operate software across backend services, data, and user interfaces. You learn unfamiliar technologies quickly.
 * Architectural judgment. You can define clear system boundaries and weigh delivery speed, reliability, and long-term maintainability as products evolve.
 * Product sense. You work directly with users to figure out which problems are worth solving and what success looks like. You make complicated workflows easy for the people using them.
 * AI-native execution. You use coding agents to multiply your productivity and tackle more ambitious work, combining faster execution with the judgment and verification needed to ship reliable software.
 * Technical leadership. Youve led complex projects hands-on, aligning collaborators and stakeholders around clear decisions. You make other engineers more effective by mentoring them and by building AI-native tools and processes that remove recurring blockers.

What Youll Need To Learn Quickly

 * How benefit verification and prior authorization work across providers, pharmacies, payers, and pharmacy benefit managers.
 * Where medication-access workflows break and how those failures affect patients, clinical teams, and operations.
 * How our product, workflow, and AI systems interact within healthcare data and reliability constraints.
 * How customers evaluate success across turnaround time, accuracy, approval outcomes, and operational effort.