Staff Software Engineer | Platform Team
MachinifyRemote - US$220k – $245kPosted 21 March 2026
Job Description
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
We’re seeking a skilled
Staff Platform Engineer
to join our team!
The Platform team builds the foundation every engineer at Machinify works on top of. Our scope is unusually broad: developer tooling and shared standards, observability and resilience engineering, core product server systems, and a growing Rust framework for building correct services fast. We lead AI tool adoption across the entire company. This is a staff-level IC role — you'll have real influence over technical direction without managing people.
We're honest about the challenge. We inherited complex and important Scala systems that need scaling work and data layer rethinking. Some of the work is untangling implementation issues so the real architectural problems become visible. If you're the kind of engineer who finds that satisfying — seeing through symptoms to root causes, making hard systems better — this is your team.
We have strong opinions about how engineering should work. Emotional safety matters. We lead with empathy for our users and our colleagues. We own the whole problem, not just the interesting parts. We build it right, test it thoroughly, and leave things better than we found them. We operate with high trust and high autonomy, and we're looking for people who thrive in that environment.
Does this sound like the right opportunity to explore?... Lets connect!
What You’ll Do
Some or all of the following:
Dig into inherited Scala systems to find where the real problems are, separate symptoms from causes, and make them scale
Redesign the data layer our ML and AI products depend on — this is an open, hard problem
Build out a Rust framework that lets teams ship correct, performant services without reinventing fundamentals
Improve observability and resilience across the platform so we find problems before our customers do
Shape developer tooling and engineering standards — your work multiplies everyone else's effectiveness
Drive AI tool adoption across the company, figuring out what actually helps engineers work better
Work across the full stack: JVM (Java/Scala), Rust, Python, SQL, and Spark
What You Bring
What matters most:
Systems thinking. You see how pieces connect. When something breaks, you reason about the whole system, not just the component in front of you.
Fearless code reading. You can drop into a large, unfamiliar codebase, build a mental model, and figure out what needs to change.
Empathy for users. Whether it's a developer using your framework or an operator reading your error messages, you design for the people downstream.
Testing discipline. You test thoroughly not because someone requires it, but because you've shipped enough software to know what happens when you don't.
Comfort with ambiguity. Our hardest problems don't come with specifications. You're energized, not paralyzed, by that.
Technical skills
Proficiency in JVM ecosystem (Java, Scala)
Experience with Rust highly desired
Python
SQL and data processing (Spark or similar)
Distributed systems design
Observability and resilience engineering
What We Offer
Work from anywhere in the US! Machinify is digital-first.
Top Medical/Dental/Vision offerings
FSA/HSA
Tuition reimbursement
Competitive salary, 401(k) with company match
Unlimited PTO
Additional health and wellness benefits and perks
Flexible and trusting environment where you’ll feel empower ... (truncated, view full listing at source)
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