Forward Deployed / Solutions Engineer

Every day, millions of hospitalized patients who need intervention are missed because clinicians simply can't see everything. HealthLeap is building the AI operating system that helps care teams identify these missed patients, enabling them to improve health outcomes and generate millions of dollars. HealthLeap is changing what is possible: closing gaps that traditional workflows and clinician capacity could never.

Over the past year, we've grown contracted revenue more than 13x, expanded rapidly across leading health systems, and now help care teams identify patients across millions of inpatient encounters.

We're ~25 people. >$32M raised. SF-based, hybrid-friendly. And, we're delivering results that are changing lives.

Own how HealthLeap connects to every hospital.

We tell clinicians which patients need attention first, so patients get care sooner. None of it works until a hospital’s data reaches us, correct and on time. That’s deep backend work: the pipelines that move patient data in real time, the integrations with the record systems hospitals run on, and the infrastructure that keeps it all reliable. You’ll also work directly with hospital IT and clinical teams, on calls, working out what’s needed and earning their trust.

You’re a strong backend engineer. You’ve designed and run real production systems and data pipelines, and you like making two systems that were never meant to talk to each other work together and stay working. You’re also comfortable in front of a customer, on a call with a hospital’s IT team, working out what’s actually going on and then building the fix. When a task comes up twice, you build the thing that does it for you. You own the problem, you don’t wait for the ticket.

We’re live at 18 hospitals today. The plan is 44 in the next three months, and another 100 in the six after that. Every one streams patient data to us in real time, and the risk scores clinicians act on are only as good as that data. Scaling that, the pipelines, the infrastructure, the reliability, is the core problem you own.

• Build and scale the data pipelines that pull patient data from each hospital and keep it flowing in real time

• Scale the infrastructure so 8x the hospitals doesn’t mean 8x the fires: monitoring, alerting, reliability

• Stand up new integrations with the record systems hospitals run on, and go deeper on the ones we already support

• Turn getting a hospital live into software, so the next one is faster than the last instead of a fresh project every time

• Build the internal tooling, and a portal hospitals log into to self-test their data, that keeps every integration easy to watch and quick to fix

• When a number looks wrong, work out why, from the hospital’s system through to what clinicians see, and fix it

We build and run our own systems here. The stack is Python and TypeScript.

• Deep backend engineering, 5+ years. You’ve designed, built, and operated production services, data models, and APIs.

• A big part of your work has been integration engineering: connecting systems that weren’t built to talk to each other (the kind of work companies like Plaid, Stripe, or Merge are built around)

• Customer-facing. You can hold your own on a call with a hospital’s IT or clinical team, scope what’s needed, and explain the tradeoffs

• You debug fast: drop into a system you’ve never seen and work out how it behaves from the code, the logs, and the data

• You build tools to kill your own busywork.

• Strong SQL and a real feel for whether the data is right

• You move fast and own the outcome

• You’ve founded a company, or were an early engineer who owned the messy parts

• Healthcare or EHR integration experience (HL7, FHIR). Useful here, but the backend and data instinct matters more.

• You get a lot out of AI tools

• You’d rather maintain an interface than build the system

• You want the spec handed to you

• You want to stay purely heads-down. You’ll be in front of hospital teams regularly, on calls and in the detail with them.

• You want predictable 9-to-5 hours. We protect deep rest, but a hospital go-live can mean a 60+ hour week.

Our interviews look like the real job. No leetcode, no puzzles. Use the tools you’d use on the job, AI included.

1. Intro call - Get to know each other

2. Technical 1 - System design

3. Technical 2 - Live coding

4. Onsite - Meet the team in SF

We decide the same week as the onsite. If it’s a fit, you’ll know fast.

• Salary: $200,000 - $275,000 base

• Equity: Meaningful ownership in an early-stage company

• Healthcare: 100% of premiums covered

• PTO: Unlimited, 20-day minimum

• 401(k): 4% match

• Equipment: Laptop and a home office budget

San Francisco, in person. Default is every day, and the flexibility is real: no tracking, no approvals, just drop “wfh today” in Slack when you need it. Rule of thumb is about 32 hours a week in the office. We judge output, not hours.

If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.