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Arlo is rebuilding health insurance from the ground up using AI. The healthcare experience today is expensive, confusing, and often so frustrating that people delay the care they need. We’re changing that by reimagining what a health plan should be: a proactive partner that enables health rather than denying it. Our AI-native platform delivers continuous, personalized support for members—helping them navigate benefits, schedule appointments, access high-quality care, and avoid financial fear. Powered by the industry’s most advanced risk-pricing engine, Arlo is already scaling fast: we’ve grown to $XXXM in premiums, cover tens of thousands of people, and see accelerating demand across brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, our team combines deep industry expertise (Palantir, YC) with the ambition to modernize a $1T market.
Job Responsibility:
Architect and ship new AI-native features that serve tens of thousands of members
Build and deploy sophisticated LLM-powered agents that autonomously reason through complex healthcare workflows
Evolve our core AI stack by advancing our capabilities in prompt orchestration, context engineering, retrieval systems, and evaluations
Develop an intelligent experience that helps patients understand their symptoms and guides them to the right setting of care (ER, Urgent Care, or PCP)
Build a conversational AI to help patients understand their health, from decoding lab results to clarifying treatment plans
Pioneer an outreach tool that analyzes claims data to send personalized, timely campaigns for preventive screenings and medication adherence
Requirements:
Demonstrated experience shipping full-stack AI products, from backend infrastructure (Python, Postgres) to production LLM applications
A strong product intuition and deep intellectual curiosity, with a passion for building 0-to-1 experiences in a fast-paced startup environment. You own problems end-to-end
A pragmatic approach to LLM safety and reliability, with hands-on experience implementing guardrails, red-teaming, and creating evaluation frameworks to manage trade-offs between performance, cost, and latency
Fluency with AI-assisted engineering tools (e.g., Cursor, Copilot) to accelerate your development workflow
Nice to have:
Experience with our front-end stack (TypeScript, React)
Familiarity with deploying AI workloads on a major cloud platform (AWS, etc.)