Staff Software Engineer

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 operational problems end-to-end: product architecture, backend systems, frontend experiences, AI workflows, and production deployment. What You Will Do Design and ship full-stack products across the insurance lifecycle, working across React, React Native, TypeScript, Python, Postgres, and modern AI infrastructure. Build AI-native underwriting systems that synthesize risk, structure messy data, and assist decision-making. Create claims tooling that automates review, coordination, and document processing workflows. Develop internal operational platforms for teams managing millions in premiums and healthcare spend. Build member-facing products that combine conversational AI, navigation, and real-time healthcare workflows. Design retrieval, memory, and evaluation systems that improve reliability and operational performance over time Work directly with operational teams to identify bottlenecks and rapidly ship systems that eliminate manual work. Own projects end-to-end: product architecture, backend systems, frontend experiences, AI integration, and production deployment. The work is highly applied. Success is measured by whether the systems you build become core infrastructure for how the company operates, reducing operational overhead, improving member experience, and allowing teams to scale far beyond traditional insurance companies. What We’re Looking For We’re looking for highly autonomous, product-minded engineers who can take ownership of an operational domain and turn messy real-world workflows into scalable software systems. Staff Engineers at Arlo work directly with teams across underwriting, claims, premium finance, member experience, and broker operations to deeply understand how the business works and where AI can create leverage. The role is highly hands-on: designing systems, shipping products, integrating AI workflows, and rapidly iterating with the people using what you build. You Have: Strong 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 The expectation for Staff Engineers is ownership and operational impact: building systems that materially improve how a function inside the company operates. Nice to Haves Experience in regulated industries (healthcare, fintech, etc.) Strong sense of design and attention to UI detail Target Compensation $250,000 – $275,000 + equity   Why Join Arlo: High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company. Join an important mission: Your work directly influences how people access care and improves lives at scale. Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity. Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare. High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition. Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process. Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law. 🔒 Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: [email protected] .

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