We are seeking a Senior Manager of Software Engineering to build and lead a new product engineering team in San Diego, developing software for providers in the sleep health diagnostics domain.
This is a people-first leadership role for an engineering leader who has previously built or scaled a team, not simply inherited one. You will be responsible for hiring, developing, and retaining a high-performing team; partnering with Product and Design on roadmap and execution; and maintaining a high bar for engineering quality, delivery velocity, and enterprise alignment. The team will operate under an AI-native product/software development methodology, and you will be responsible for establishing what disciplined, high-quality AI-assisted delivery looks like from day one. You should be technical enough to earn the team's credibility, while ultimately measured by the team's output rather than your own.
This is a foundational role. You are not inheriting a running team — you are building one.
What You'll Do
Build the Team
- Lead the hiring and onboarding of engineers across levels, with a focus on San Diego-based talent.
- Establish team norms, operating cadences, and a culture of ownership and craft from the team's inception.
- Identify capability gaps early and address them through hiring, development, or cross-team partnership.
Drive Delivery
- Own the team's end-to-end delivery, including planning, execution, and operational health.
- Partner with Product Management to translate strategy into a sequenced, achievable roadmap for provider-facing sleep health diagnostics solutions.
- Maintain a high standard for quality, security, and compliance while balancing delivery pace.
- Identify and remove delivery blockers, escalating appropriately when required.
Establish AI-Native Development as the Team's Default
- Stand up and continuously refine an AI-native product/software development methodology for the team, from specification through code through review.
- Ensure the team builds on enterprise architecture blueprints, shared platforms, and DevX standards.
- Create the conditions for disciplined AI-assisted engineering practices to take hold, with correctness, security, and maintainability treated as non-negotiable.
- Conduct or delegate rigorous design and code reviews, making engineering standards visible and consistent.
Lead Across the Organization
- Represent the San Diego team in cross-functional forums with clarity and credibility.
- Build effective working relationships with peer engineering managers, platform teams, and enterprise architects.
- Surface risks, dependencies, and trade-offs early to enable timely decision-making.
Develop Your Engineers
- Conduct regular 1:1s, calibrations, and growth conversations.
- Sponsor stretch assignments and create visibility for strong performers.
- Build a team capable of developing its own Staff and Senior engineers over time.
What You Bring
- 8+ years of software engineering experience, including 3+ years in engineering management.
- Demonstrated experience standing up a team or function, not solely managing an existing one.
- A track record of hiring and retaining strong engineers in competitive markets.
- Sufficient technical depth to make credible architecture and staffing decisions (backend and/or full-stack preferred).
- Hands-on experience or strong working knowledge of AI-native/AI-assisted software development practices and tooling (e.g., Claude Code, Copilot, Augment Code).
- Experience partnering with Product and Design within an agile, product-led delivery model; healthcare or health-tech experience is a plus.
- Strong written and verbal communication skills, with the ability to operate effectively up, down, and across the organization.
- Demonstrated ability to establish structure and process in an ambiguous, early-stage environment.
What We Value
- Managers who build team capability rather than personal dependency.
- Leaders who provide engineers with context and the autonomy to act on it.
- Hiring managers who select for potential and invest deliberately in growth.
- Operators who sustain delivery momentum without compromising team health.
- AI-native leaders who treat new methodology and tooling as a team advantage from the outset.
