Principal Software Engineer
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.
For more information, visit
arcadia.io.
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.
What Success Looks Like
In 3 months
- 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
In 6 months
- 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
In 12 months
- 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
What You'll Be Doing
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
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
What You'll Bring
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
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
Would Love for You to Have
Tech You'll Work With
Arcadia's platform processes petabyte-scale healthcare data through a lakehouse architecture built on open table formats. Apache Spark drives distributed compute; dbt drives transformations; Kafka moves streams; Cassandra/Scylla handles high-throughput storage; OpenSearch / Elasticsearch powers search and indexing - all orchestrated on Kubernetes in AWS, with services spanning TypeScript/Node, Python, Go, and Java/Kotlin (polyglot, by design).
We're actively expanding this entire platform-stack to be AI-native - enabling the creation of custom agents built on Arcadia's data foundation to solve some of healthcare's biggest challenges. Principal Engineers shape the patterns here. Depth in distributed compute, data infrastructure, or platform engineering translates directly.
What You'll Get