**About Us:**
We’re partnering with Fedora Solutions, a leading medical billing company that
supports 40%+ of independent oncology clinics in the U.S. Their team of 3,000+
offshore billers handles high-complexity revenue cycle work every
day—authorizations, charge entry, coding, submissions, denials, and appeals.
We are an independent startup building the technology layer on top of that
operational expertise. Using 20+ years of real-world billing data and
workflows, we’re consolidating institutional knowledge into an internal
platform focused on automation and quality testing. While we’re starting with
a platform built for our investor/strategic partner, it’s designed from day
one with a clear path to becoming a B2B SaaS product for the broader medical
billing market.
**Who We’re Looking For:**
We’re looking for a hands-on engineer who wants ownership in a complex
operational domain and the chance to build the technical architecture from the
ground up. You should be comfortable spanning data pipelines, backend systems,
workflow engines, and internal tooling and turning real-world processes into
clear, reliable abstractions.
**The Engineering Challenge:**
You’ll turn messy, exception-heavy oncology billing workflows into clean,
testable systems that thousands of people depend on daily. This is systems
engineering under real constraints: correctness, auditability, observability,
and change control, plus the opportunity to layer in AI once the foundation is
strong enough to support it reliably.
**Technical Vision:**
* Cloud infrastructure + core data platform (secure-by-default, built to scale)
* Production-grade ingestion + transformation pipelines with observability (quality checks, lineage, alerts, SLAs)
* Workflow + rules engines encoding real decision logic (versioned, auditable, testable)
* Automation services that remove repetitive operational work and integrate with existing systems
* AI capabilities on top of clean workflows/data (denial-risk prediction, missing-document detection, correction suggestions, measurable accuracy + monitoring)
This is a chance to build foundational systems inside a high-throughput
operation: guaranteed users, clear constraints, and a direct line from
engineering work to measurable outcomes.
**Team + Environment:**
* You’ll work directly with the Founder in a high-trust, low-ego environment with fast decisions and real ownership.
* Early-stage energy: you’re a key builder, close to customers/operators, shipping things that immediately matter.
* We value craft + momentum: clean systems, small releases, and celebrating wins (and learning quickly from misses).
* Strong feedback culture: candid, kind, and focused on making the work (and the team) better every week.
**Core requirements**
* 2–5ish years experience, strong fundamentals, high ownership mindset
* Experience building and scaling production systems end-to-end
* Strong grasp of APIs, webhooks, async job pipelines, auth, data modeling
**BONUS**
* Built configurable workflow/rules engines (decision trees/branching, checklists, escalations) with auditability and human override.
* Strong data engineering: cloud warehouse design + secure ETL/ELT pipelines with dedupe/normalization, schema evolution, and monitoring.
* Proven security/compliance mindset (HIPAA-aligned): RBAC/IAM, encryption, logging, lineage/versioning, and immutable audit trails.
* Experience shipping automation in stages (auto-fill, validation/scrubbing, attachments/templates, reminders/escalations) with safe fallbacks to humans.
* Strong quality & reliability practices: unit/integration/data-quality tests, observability (metrics/alerts), and resilient operations in messy real-world data.
* Ability to partner with ops/domain teams to capture SOPs/edge cases and iterate using outcome metrics.
**What we offer**
Competitive compensation (Salary, Equity),
Tight-knit, highly motivated team,
Flexible remote environment,
Environment that fosters responsibility and independent thinking,
401(k),
Medical + Dental
**To Apply**
Please include brief answers to the questions below (short bullets are totally
fine). We use these to quickly identify builders who’ve shipped real systems.
Applications without answers may not be reviewed.
1. Years of full-time experience (excluding internships): 3-4 / 5-6 / 6+
2. Have you owned a production system end-to-end? Yes / No. If yes: what was it, and what parts did you personally own? (1–2 lines)
3. List 2–3 things you’ve built in production (e.g., APIs, webhooks, async jobs, auth, data models, observability).
4. Describe your most relevant data pipeline work (what the data was, scale, and what you built, 1–2 lines).
5. Healthcare / HIPAA-aligned work: Yes / No. If yes: what kind of system and what data did it touch? (1–2 lines)
6. Have you worked in a scrappy environment before? Yes/No