Principal Engineer

Architect — set the direction. Assess the current stack, define the target architecture for the rebuild, and turn strategy into a concrete, sequenced plan the team can execute. 

Build — write the code, not just the spec. This is a hands-on role. You write and review the core code yourself, especially in the early days, rather than delegating it away. 

Scale — make it last. Build a platform and a small team that can carry Dozee’s growth for years, on lean resources, without re-architecting from scratch every stage. 

Own the technical vision and roadmap — assess the current platform, define the target AI-native architecture, and set a sequenced plan the team can build against. 

Write and ship production code — be in the codebase daily as a hands-on principal engineer, not just producing design documents for others to build. 

Rebuild the platform around modern AI technologies — apply the latest AI and LLM tooling to the core platform architecture, not as a bolt-on feature but as a foundation. 

Build and lead a small, high-leverage team — start with a team of about two, hire deliberately as the platform grows, and set the technical bar and day-to-day ways of working. 

Make resourceful build-vs-buy calls — operate with limited resources, choose the highest-leverage technical bets, and avoid premature complexity.

Design for scale from day one — build an architecture that can grow with Dozee’s customer base, data volume, and clinical requirements over the long haul. 

Own platform reliability and quality — testing, monitoring, incident response, and the operational discipline that keeps a lean team sustainable. 

Partner cross-functionally — work closely with product, clinical, and go-to-market teams to translate business priorities into technical execution. 

Report progress and trade-offs to leadership — keep the Management and stakeholders informed on the roadmap, risks, and resourcing needs as the rebuild progresses. 

10+ years of software engineering experience, including senior, staff, or principal-level roles, ideally with a track record of leading a platform rebuild or greenfield build from scratch. 

Deep hands-on experience applying modern AI and LLM technologies to production systems, not just prototypes or proofs of concept. 

Experience architecting and scaling platforms in a resource-constrained environment — an early-stage startup, a small team, or similar. 

A track record of both writing code and leading or mentoring a small engineering team, comfortable doing both at once. 

Experience owning a system end to end, from architecture through deployment, monitoring, and iteration. 

Exposure to healthcare, medical devices, or other regulated, high-stakes production environments (FDA, HIPAA) is a plus. 

Builder mindset. You’re comfortable building a platform from zero with limited resources rather than inheriting an established team and stack. 

Hands-on technical depth. You write and review code at a high bar — this role leads by doing, not just by directing. 

AI-native architect. You have deep fluency with the latest AI and LLM tooling and know how to embed it in a production platform, not just a demo. 

Pragmatic judgment. You choose the simplest architecture that scales and resist premature complexity or over-engineering. 

Long-term thinker. You design for the next several years of growth, not just the next sprint or the next customer. 

Lean-team leadership. You know how to get a small team — starting at two — punching well above its size.

Ownership at founder speed. You move fast, make calls with incomplete information, and take responsibility for outcomes. 

Clear communicator. You translate deep technical trade-offs into terms leadership and non-technical stakeholders can act on.