Full Stack AI Engineer

June 22, 2026

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<h2>ABOUT OUTMARKET</h2>Outmarket is the AI platform for insurance, trusted by more than 250 brokerages to run the work their business depends on. Commercial insurance still runs on dense documents and slow, manual workflows, and that is exactly what we automate: quote comparisons, coverage gap and tower analysis, policy review, and proposal generation, all grounded in our customers’ own data and source-cited so teams can trust the output.The impact is concrete. Teams save 12 to 15 hours per person every week, cut errors by roughly 65 percent, and win more business, all on infrastructure that is SOC 2 Type II certified, single-tenant, and never used to train AI models. We are an AI-first company in both what we build and how we work, shipping quickly and in close partnership with the agencies that rely on us.WHAT YOU’LL GET<ul style="min-height:1.5em"><li>A high-impact role with ownership from day one.</li><li>Competitive compensation and meaningful equity.</li><li>Direct collaboration with founders and real users.</li><li>Remote-first flexibility.</li><li>The opportunity to help build an AI-native product from the ground up.</li></ul>ABOUT THE ROLE We are hiring a Full Stack AI Engineer to work across the product and technical stack, from AI workflows and backend systems to frontend product experiences. This is a build-and-run role for someone who likes moving between customer problems, product thinking, and hands-on implementation.WHY THIS ROLE<ul style="min-height:1.5em"><li>Work across a broad technical stack in an AI-native environment.</li><li>Build features that directly affect real customer workflows and outcomes.</li><li>Partner closely with founders and experienced engineers.</li><li>Move quickly from idea to shipped product.</li></ul>WHAT YOU’LL DO<ul style="min-height:1.5em"><li>Work directly with insurance brokers, MGAs, and carriers to deploy AI-powered solutions.</li><li>Use modern LLMs, embeddings, and structured data pipelines to build features such as document review, entity extraction, and quote comparison.</li><li>Rapidly prototype and productionize features based on customer needs and feedback.</li><li>Build reusable systems and components that scale across use cases and customers.</li><li>Operate across boundaries, whether product, infrastructure, workflow logic, or delivery.</li></ul>WHAT WE’RE LOOKING FOR<ul style="min-height:1.5em"><li>2+ years in ML/NLP/LLM systems, or 3+ years in software engineering with strong applied-AI interest.</li><li>Proficiency in Python and experience integrating modern LLMs into products.</li><li>Experience with SQL and database systems.</li><li>Ability to turn messy real-world data into practical product capabilities.</li><li>Strong ownership and comfort shipping without a perfectly bounded problem.</li></ul>BONUS IF YOU HAVE<ul style="min-height:1.5em"><li>Experience with unstructured documents such as PDFs or insurance policies.</li><li>Depth in Postgres, React, or Python.</li><li>Early-stage startup experience.</li></ul>

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