Arlo

Health Insurance

StaffSoftwareEngineer

$230–250k New York, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Staff Software Engineer at Arlo. Skills: Full-stack product development, AI-native system design, System ownership end-to-end, Operational problem solving. Design and ship full-stack products across the insurance lifecycle. Build AI-native underwriting systems”

What You'll Achieve.

Become core infrastructure for how the company operates; Reducing operational overhead; Improving member experience; Allowing teams to scale far beyond traditional insurance companies

Industry & Context.

Health Insurance
Problems you'll solve

Turn messy real-world workflows into scalable software systems; Identify bottlenecks and rapidly ship systems that eliminate manual work

What They're Looking For.

Must Have

experience building and shipping full-stack products across modern infrastructure (Python, Postgres, TypeScript, React/React Native), Excellent product and engineering judgment in ambiguous environments, The ability to independently own large systems from idea to production, High standards for execution, velocity, and code quality

Nice to Have

Experience in regulated industries (healthcare, fintech, etc. ), sense of design and attention to UI detail

What You'll Do.

Design and ship full-stack products across the insurance lifecycle

Build AI-native underwriting systems

Create claims tooling

Develop internal operational platforms

Build member-facing products

and evaluation systems

Work directly with operational teams to identify bottlenecks and rapidly ship systems

Own projects end-to-end: product architecture

and production deployment

How You'll Work.

Team & Collaboration

Work closely with operational teams; Work closely with AI Forward Deployed Engineers; Work directly with operational teams; Work directly with teams across underwriting, claims, premium finance, member experience, and broker operations; Rapidly iterate with the people using what you build; High collaboration; Works closely, openly, and with ambition

Process & Methodology

Own projects end-to-end

Full Job Description

Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial. Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut. AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves. We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators. About the Role We’re looking for Staff Software Engineers to help build the systems that power an AI-native insurance company. Insurance operations are sprawling: underwriting, claims, premium finance, broker operations, member support, care navigation, and more. Most companies run these functions through fragmented vendors, legacy software, and manual workflows. At Arlo, we build our own infrastructure. You’ll work closely with operational teams and AI Forward Deployed Engineers to turn real business workflows into AI-native products and internal platforms. The goal isn’t to bolt AI onto existing software; it’s to redesign how the work happens altogether. We care about engineers who want to own real operationa

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