About SiPhox Health
SiPhox Health is building the leading home testing platform for biomarkers across inflammation, hormones, and metabolic and cardiovascular health. Six in ten Americans live with a chronic disease, and our mission is to make early detection possible from home.
We operate two business lines, both scaling quickly:
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Mail-in blood testing: Growing more than 50% quarter over quarter, and the most comprehensive and highly rated at-home blood testing available today.
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At-home blood testing device: Planned launch in 2027–28. Our chip-based module combines biochemistry with integrated photonics, electronics, and microfluidics, protected by more than 50 patents.
SiPhox is an MIT startup backed by Tier I investors including Y Combinator, Khosla Ventures, and Intel Capital.
Position Summary
We're looking for a hands-on engineering lead who has strong AI-enabled development experience, run an AI-enabled software development lifecycle, and led a small team to ship distributed systems in production. You've operated across the stack, owned services from architecture through deployment, and know how to move fast without breaking the discipline that keeps complex systems reliable. This is a player-coach role: you will remain hands-on in the codebase while leading the team and owning how the team builds software.
What You Will Do
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Lead an AI-enabled development process: Own and continuously improve how the team builds software with AI coding tools and agents integrated across the lifecycle — from spec to review to deploy. Set the standards and workflows that enable a small team to deliver well beyond its size.
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Design the development process: Define and evolve our SDLC — version control, code review, CI/CD, automated testing, and observability — so the team ships quickly and reliably.
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Lead and grow a small team: Manage, mentor, and set technical direction for a small team of engineers. Balance hands-on coding with unblocking others, reviewing work, and raising the team's standards.
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Design and ship distributed systems: Own the architecture and implementation of backend services and full-stack features that scale across our platforms, from data ingestion pipelines to user-facing applications.
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Collaborate across the stack and the org: Partner with clinical, sales, finance, and operations teams to turn complex requirements into reliable, well-designed software.
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Support data, operational, and financial reporting: Build and maintain complex datasets and data pipelines that power operational and financial reporting across the business.
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Own the full lifecycle: Take features from design through implementation, testing, deployment, and observability in production.
Minimum Qualifications
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Experience: 5+ years building production software as a full-stack engineer, including experience leading projects or a small team.
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AI-enabled development: Hands-on experience integrating AI coding tools and agents into a real development workflow, and managing an AI-augmented software development process end to end.
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Process design: Demonstrated track record designing and running SDLC practices — version control, code review, CI/CD, and automated testing — that help a team ship faster, not slower.
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Team leadership: Experience managing or mentoring a small team of engineers.
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Distributed systems depth: Demonstrated history of designing, deploying, and scaling distributed systems on AWS (or GCP/Azure). Strong grasp of the fundamentals.
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Full-stack range: Comfortable owning both backend services and front-end experiences.
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Data and reporting: Experience building complex datasets and supporting operational and/or financial reporting.
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Communication: Ability to articulate technical trade-offs to engineers while clearly explaining product decisions to clinical, finance, and sales stakeholders.
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Evidence of exceptional skill: A portfolio, open-source contributions, or shipped products that demonstrate exceptional ability.
How We Work
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Bias for action: We expect you to prototype quickly and iterate in tight loops.
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Extreme ownership: You're responsible for products end-to-end: design → implementation → testing → observability.
Compensation and Benefits
- Stock options, and meaningful equity in a company solving a problem that matters.
