Principal Software Engineer

Arcadia

1d•$250,000 - $350,000

About The Position

Arcadia is dedicated to happier, healthier days for all. We believe that there is a better healthcare world – one powered by data. Our platform transforms complex, diverse data into a unified foundation for health, helping organizations deliver better care, boost revenue, and lower costs. We’re a team of fiercely driven individuals committed to making healthcare more sustainable—and we’re looking for passionate people to help us get there. Why This Role Is Important to Arcadia 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.

Requirements

A track record as the technical owner of cross-team or platform-level initiatives — multiple systems you've taken from ambiguous beginnings through long-term operation, with concrete examples you can walk us through
Deep technical foundations across distributed systems, data infrastructure, and service architecture — you reason from first principles, anticipate failure modes, and recognize architectural drift before it compounds. You are the person teammates escalate structural calls to, and the one who catches when an AI-generated design is plausible but wrong
Proven ability to own complex systems from design through rollout and long-term operation — including the unglamorous middle (observability, on-call, migration paths, deprecations)
A track record of identifying and driving non-obvious technical investments — improvements to the stack, reliability, or platform capability that you spotted, evaluated, and shepherded through the decision
Demonstrable depth with agentic AI-assisted development — actively using agentic coding tools, context-engineered environments, and AI-augmented workflows, with examples of AI-native tooling, custom agents, or team patterns you've built, shipped, or substantially shaped. The work needn't have happened at your current employer — what matters is that the depth is real, the engineering judgment driving it is yours, and you can walk us through both in detail, including specific cases where you caught the agent producing plausible-but-wrong work and corrected course
Track record of mentoring and coaching Senior Engineers to higher levels of judgment and impact — not just answering questions, but visibly raising their bar over time
Strong customer and product orientation — comfortable engaging directly with customers, partners, or downstream consumers to define problems before building and validate outcomes after shipping
Clear written communication — design docs, reviews, and post-release writeups that establish standards beyond your immediate work
Demonstrated influence across team boundaries through technical credibility rather than positional authority

Nice To Haves

Experience defining org-wide AI adoption strategy — what was adopted, what was rejected, what got measured, and what the org actually changed about how it builds
Healthcare technology, HIPAA-regulated environments, or other regulated data domain experience
Track record of incubating new product directions or greenfield platform capabilities from ambiguous starting points
Speaking, writing, or open-source presence that reflects broader technical influence

Responsibilities

Owning complete vertical slices of cross-team or platform-level work — including the multi-quarter migrations, deprecations, and architectural pivots that single-team scope can't carry
Setting the technical bar for what "right" looks like in your domain — sharpening designs, catching architectural drift (including in AI-generated work), and shaping the patterns the team builds toward
Proactively identifying and evaluating platform-level opportunities — new architectures, tools, or capabilities that improve reliability, customer outcomes, or what we can credibly take to market — and driving them to a decision with evidence, alternatives, and tradeoffs
Defining SLOs and observability for what you ship; sharing on-call ownership as a baseline expectation, not an escalation path
Leading the rearchitecture of legacy or high-debt areas where the right call is structural — and seeing the migration through to deprecation
Driving the team's adoption of agentic AI-assisted development — building internal tooling, defining workflows, and setting the standard for what AI-native engineering looks like at Arcadia
Engaging directly with customers and partners during incidents, design reviews, and major rollouts — closing the loop between what we build and what they actually experience
Mentoring Senior Engineers through code review, design partnership, and direct coaching — the trajectory of the engineers you coach is part of how your impact is measured
Influencing engineering practice across teams — architecture standards, operational excellence, AI strategy — through written guidance, working examples, and direct involvement in the hardest problems