Job description

FOUNDING ENGINEER, BACKEND & INFRASTRUCTURE ABOUT BACKBONE Care should be paid for the moment it’s delivered. At Backbone, we’re making that possible for the first time by building the clinical AI layer for healthcare payments. Today, U.S. healthcare wastes more than $350B yearly on administrative work that has nothing to do with patient care: prior authorizations, denials, appeals, and the staff hired on both sides of the aisle to adjudicate and determine payment for services rendered. As a result, patient care is delayed, clinicians burn out, margins crater, and hundreds of billions of dollars that should be funding care end up funding the friction itself. Backbone is dismantling this friction, building intelligent financial rails atop clinical AI research to facilitate instant payments between payers and providers. We're backed by Andreessen Horowitz (a16z), Lightspeed, Hanabi, and a roster of operators and clinicians who have built and run the largest payers, providers, and healthcare technology platforms in the country. Our founder/CEO, Manan Shah, holds a BS/MS in Math & CS from Stanford and led ML infrastructure at Sequoia-backed Kumo AI, where he built graph neural networks serving DoorDash, Reddit, and Coinbase. Backbone’s revenue is growing quickly, customer demand is outpacing our team, and the road ahead is bright. WHAT YOU’LL DO As a founding engineer, you’ll own the systems that make Backbone work: chart ingestion, document processing, claims workflows, browser and computer-use automation, payer portal navigation, orchestration, queues, reliability, auditability, and the infrastructure needed to scale from thousands of charts and claims to hundreds of thousands. You will: - Build and scale the distributed systems that power Backbone’s clinical and financial workflow; own backend services across chart data, claims data, authorization workflows, denial workflows, and payer/provider integrations - Build orchestration infrastructure for long-running, failure-prone workflows across EHRs, practice management systems, clearinghouses, and payer portals - Work on browser-use and computer-use systems that navigate complex medical software and payer portals - Design reliable systems for messy healthcare data: scanned charts, PDFs, structured claims, unstructured notes, attachments, policies, and operational state - Build observability, retry, audit, and human-in-the-loop infrastructure for high-stakes production workflows - Partner with product and research engineers to take new clinical intelligence capabilities into production, and set the engineering patterns that future engineers will inherit WHAT WE’RE LOOKING FOR - 3+ years of professional software engineering experience shipping production systems end-to-end - Generalist range across backend, data, and ML, alongside real LLM experience in production - Comfort with distributed systems, microservices, queues, workflow engines, data pipelines, or large-scale backend infrastructure Healthcare experience is helpful, but not required. Curiosity, rigor, and taste matter more. WHY JOIN This is a chance to join early and help define both the product and the engineering culture. You’ll work on hard, practical problems: turning fragmented healthcare workflows into software that actually helps people do their jobs faster and better. Your work will touch product decisions, system architecture, user experience, and the core automation engine behind Backbone. We offer competitive compensation, meaningful ownership, and the opportunity to build foundational technology in a massive, broken, high-impact industry.

Requirements

Must-haves

Build orchestration infrastructure for long-running, failure-prone workflows across EHRs, practice management systems, clearinghouses, and payer portals
Work on browser-use and computer-use systems that navigate complex medical software and payer portals
Design reliable systems for messy healthcare data: scanned charts, PDFs, structured claims, unstructured notes, attachments, policies, and operational state
Build observability, retry, audit, and human-in-the-loop infrastructure for high-stakes production workflows
Partner with product and research engineers to take new clinical intelligence capabilities into production, and set the engineering patterns that future engineers will inherit
3+ years of professional software engineering experience shipping production systems end-to-end
Generalist range across backend, data, and ML, alongside real LLM experience in production
Comfort with distributed systems, microservices, queues, workflow engines, data pipelines, or large-scale backend infrastructure
Healthcare experience is helpful, but not required. Curiosity, rigor, and taste matter more.
This is a chance to join early and help define both the product and the engineering culture.
We offer competitive compensation, meaningful ownership, and the opportunity to build foundational technology in a massive, broken, high-impact industry.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlllm

Platform: ashby
Effort: quick