Senior Software Engineer, AI Engineer Hybrid - SF Bay Area

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. We're a fast-growing, mission-driven company building the infrastructure and products that define this new category of care.

• Hybrid by design. Two days a week in-office (Tuesday and Thursday) in Palo Alto or San Francisco. 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.
• Low-ego, high-curiosity. We approach disagreement with humility and technical rigor, not politics. We invest in each other's growth.
• Outcome-oriented. We move fast, own our work end-to-end, and balance speed with the durability that healthcare demands.

AI is reshaping how clinical care is delivered, and Midi is building the products at the frontier of that shift. You'll build AI-powered features and systems that genuinely change clinician and patient experience — from clinical workflow automation to patient-facing assistants to back-office intelligence — grounded in the realities of healthcare-grade safety and evaluation.

• Design, build, and ship LLM-powered features end-to-end: prompt design, retrieval, tool use, agents, evaluation, and production operations
• Build the evaluation harnesses and feedback loops that let us ship AI features responsibly
• Integrate AI capabilities deeply into patient, clinician, and operational workflows
• Partner with clinical, product, and safety stakeholders to define what "good" looks like
• Contribute to our internal AI-for-engineering practices and tooling
• Stay close to the research and ecosystem; bring the best of it back to the team

• 6+ years of software engineering experience, with meaningful recent time building production LLM / ML features
• Strong hands‑on coding skills in Python; comfortable across the full stack when the feature demands it
• Seasoned at system design for AI systems: retrieval, orchestration, caching, evaluation, cost and latency tradeoffs
• Deep, hands‑on command of modern AI coding tools — you're a strong follower of the frontier and apply new techniques quickly
• Good mentorship instincts; generous with what you learn
• Rigorous about evaluation and safety; allergic to vibes‑only launches
• Strong communicator; comfortable explaining model behavior to non‑technical stakeholders

• Experience with healthcare, clinical NLP, or regulated AI deployments
• Experience building agentic systems or production RAG at scale

• Hiring Manager Screen (45 min)
• Live Technical Assessment (3 sessions: 150 min)
• On‑Site Interview and Lunch (4 sessions: 150 min)

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At Midi Health, we are committed to pay transparency and equity. The estimated salary range for this role is $170,000-$210,000 per year, based on factors such as experience and skills. In addition to base salary, employees are eligible for a wide range of benefits and equity in the company.

We believe in fair and competitive compensation practices that align with our values of equity and inclusion. If you have any questions about how we determine pay, we’re happy to discuss further in the hiring process.

At this time, Midi is unable to provide visa sponsorship.
All Candidates must be authorized to work in the United States without current or future sponsorship needs.

Midi Health is an Equal Opportunity Employer. We are committed to pay equity and ensure that all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Our compensation philosophy is based on fair, objective criteria and the impact of the role, regardless of an applicant’s salary history.

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