**About Oler Health**
We build the software that runs skilled nursing facility (SNF) operations.
Billing, case management, and the mountain of referral and clinical documents
that move patients through post-acute care. It's a domain most engineers never
see, and it's full of genuinely hard, high-leverage problems: pulling
structured data out of messy faxed PDFs, reconstructing Medicare stays from
incomplete records, and extracting key information from EMR records and
surfacing it at the right time. The work directly affects whether facilities
get paid correctly and whether patients are placed quickly.
We're a small, senior team. You'd be one of our first few engineers, with real
ownership from day one.
What you'll work on
You'll work across the stack and pick up problems wherever they're most
valuable, but the surface area includes:
Backend: Python/Django services on GCP (Cloud Run, Cloud SQL/Postgres,
BigQuery, Pub/Sub)
Frontend: React/TypeScript product surfaces that billing and clinical staff
use every day
Document intelligence: ML models and pipelines that extract structured data
from clinical and referral documents
Data engineering: billing attribution pipelines (PDPM/Medicare/Medicaid),
analytics, and the dbt-style transformation layers underneath them
**What we 're looking for**
A strong generalist who can own a problem end to end, from ambiguous spec to
shipped feature
Solid fundamentals in at least one of our core areas (backend, frontend, data,
or ML), and the curiosity to work outside it
Comfort operating with little process and high autonomy. We are an early stage
team.
Bonus: healthcare, document processing, or data-pipeline experience, though
we'll teach the domain to the right person
**How we work**
We lean hard on AI coding tools, and our view is that they raise the bar
rather than lower it. The engineers who do well here use them to move fast and
read every line with calibrated skepticism. They know when the model is
confidently wrong and they own the output as their own. If "the AI wrote it"
is ever your explanation for a bug, this isn't the right fit. If you find that
the tools let you take on bigger problems than you could before, you'll fit
right in.