Principal Software Engineer
Arcadia
Posted Today · via Lever
Job Description
Arcadia's platform is the backbone of how partners and customers act on healthcare data at national scale. Principal Engineers are the technical owners of the cross-team initiatives and platform-level outcomes that define what Arcadia's engineering organization is capable of — the engineers others look to when the right answer is structural, not incremental.
A Principal Engineer at Arcadia owns the complete vertical slice: requirements through customer validation, design through long-term operation. They raise the floor for the engineers around them through direct coaching, reusable patterns, and the tooling they leave behind. They define how the team adopts AI as a leverage multiplier — not just for their own productivity, but as a standard the team and the org can adopt.
- You have deep familiarity with your domain's platform surface, key dependencies, and the customer outcomes the team owns
- You have identified the two or three most leveraged technical investments in your area and aligned with Product, Engineering Management, and key partners on a plan
- You have established working relationships with the Senior Engineers you'll coach and the cross-team peers you'll collaborate with most often
- You are driving a multi-team or platform-level initiative end-to-end — requirements and architecture through implementation, rollout, and observability
- You are visibly raising the floor on Senior Engineer execution through design reviews, code review, pairing, and direct coaching
- You have shipped AI-native tooling, workflows, or patterns that other teams in the org have adopted, with at least one peer team actively coached on how to apply them
- You own the technical health, scalability, and customer-facing outcomes of a significant platform domain
- You are recognized cross-team for technical judgment, calibration, and the quality of the engineers whose trajectory you've shaped
- You have defined and operate a measurable bar for how engineers across multiple teams adopt agentic AI-assisted engineering — what good looks like, what to avoid, and how to spread it