Midi Health
Staff Software Engineer, Full Stack
Hybrid - San Francisco Bay Area · Staff+ · Part-time
No sponsorship$210k-$250kDetected 21 hours ago
ReactNext.jsDjangoFull-Stack DevelopmentGitCI/CDLLMsComplianceAuditingTest AutomationLeadershipCommunication
About the role
- 2 days/week in-office (Monday and Thursday) in Palo Alto or San Francisco, 3 days remote.
- We believe high-trust teams are built in person and scaled remotely. - AI-native engineering.
- We approach disagreement with humility and technical rigor, not politics.
Responsibilities
- Partner with Executive Leadership, Product, Marketing, and Clinical Stakeholders to identify unmet customer and operational needs, translating business goals into technical strategies that deliver outcomes for our patients and clinicians
- You bring a versatile background in building consumer-facing products alongside deep expertise in architecting complex operational and workflow management systems.
- You help create a respectful, low-ego team environment, approaching discussions with curiosity and humility.
- We're a fast-growing, mission-driven company building the infrastructure and products that define this new category of care.
- Hybrid by design. 2 days/week in-office (Monday and Thursday) in Palo Alto or San Francisco, 3 days remote. We believe high-trust teams are built in person and scaled remotely.
- AI-native engineering. We expect every engineer to be fluent with modern AI coding tools (Claude Code, Cursor, Copilot, and similar) and to actively push the frontier of how we build software.
- We expect every engineer to be fluent with modern AI coding tools (Claude Code, Cursor, Copilot, and similar) and to actively push the frontier of how we build software.
Requirements
- You have 10+ years of experience building and scaling complex engineering solutions, with a proven track record of leading large-scale architectural migrations in a startup environment.
- Applicants must be authorized to work in the U.S. without current or future visa sponsorship.
- All Candidates must be authorized to work in the United States without current or future sponsorship needs.
- You are comfortable operating at a high level of abstraction, translating vague product and growth goals into concrete technical roadmaps.
- You are a power-user of agentic coding tools and LLM's (e.g., Claude Code, GitHub Copilot) to accelerate development and mentor the team on high-leverage prompting and code-auditing strategies.
- While you are waiting for us to review your resume, here is some fun content to check out.
- If you have any questions about how we determine pay, we're happy to discuss further in the hiring process.
Compensation
- $210,000 - $250,000 + equity + benefits
Benefits
- We move fast, own our work end-to-end, and balance speed with the durability that healthcare demands.
- Analyze complex technical problems and lead architectural reviews across multiple teams to prevent technical debt, establish cross-service patterns, and ensure the long-term sustainability of Midi's healthcare ecosystem.
- Craft exceptional, thoughtful, scalable and flexible products and code, balancing for speed of execution and scalability
- About Midi Health
- Midi Health is the largest virtual care clinic for women in midlife navigating perimenopause, menopause, and other hormonal transitions.
- We combine expert clinicians, evidence-based protocols, and a modern technology platform to deliver care that has historically been underserved by the healthcare system.
- As we scale, you will be a hands-on technical driver, distilling complex understanding from across Midi into cohesive technical roadmaps and products that help us revolutionize women's healthcare.
Company info
- We are looking for a Staff Fullstack Engineer to serve as a technical pillar within our Engineering Org.
Visa & Work Authorization
- At this time, Midi Health is not able to sponsor or take over sponsorship of any employment visa (including H-1B, TN, or other work authorization).
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This listing is sourced directly from Midi Health's careers page and normalized into a canonical job model.