Sr. Software Engineer

About Our ClientThis is a rare opportunity to become the founding engineering leader for an AI-native company attacking a multi-trillion-dollar market that has not been meaningfully digitized in decades. You will work directly with a repeat founder, own the technical foundation, and build the operating layer that can make commercial insurance more transparent, data-driven, and software-native.Largest pre-seed in insurtech history context: Backed by $8M at pre-seed for an ambitious infrastructure opportunity.Distribution from day one: The company has access to more than half of the target market at launch.AI-native from the start: The platform is being designed around modern data access, API orchestration, document reasoning, and agentic engineering workflows.Founder-market fit: The founder is a 3x successful founder who built and scaled a highly successful $500M platform in this space, was previously recognized on the Forbes 30 Under 30 list, and deeply understands the buyer, workflows, and market structure.Massive market timing: Commercial insurance remains a multi-trillion-dollar market still powered by fragmented data and manual renewal processes.This is a founding-stage role with the scope to match. You will architect and ship the systems that turn unstructured insurance data into one of the largest datasets of its kind, with real ownership over the technical direction of a company that already has distribution lined up.You will work directly with the CTO, an experienced engineering leader from a top-tier data and analytics company, and a small founding engineering team that is actively growing. The role is hands-on and high-agency, suited to someone who wants to put up real reps on hard problems and own outcomes end-to-end.What You’ll BuildYou’ll move across three problem domains, with the expectation that you go deep in at least one:Data ingestion and enrichment: extracting structured data from heterogeneous, document-heavy sources (policies, schedules, loss runs) and joining it against 100+ external datasets.AI-native underwriting and risk modeling: building the models and workflows that turn that data into pricing intelligence and placement decisions.Owner-facing product: the surfaces where customers organize, analyze, and act on their insurance portfolios.What We’re Looking ForAn engineer who is genuinely excited about what AI unlocks in a domain that has resisted digitization for decades, and who wants to build something that hasn’t been built before.4+ years of engineering experience; someone obsessed with building who has shipped product when the team was small, the scope was undefined, and there was no one above them to escalate to.Real reps as a founding engineer or early-stage builder, or as a senior IC at a startup or on an unconventional team inside a larger company, hungry for an order-of-magnitude increase in ownership and agency.Strong full-stack range: comfortable moving between backend, infrastructure, and product surfaces, with a bias toward shipping.Comfortable with data-heavy systems: APIs, pipelines, async workflows, enrichment, and the messy work of making real-world unstructured data usable.Builds with modern AI tooling by default, and has informed opinions on where it works and where it doesn’t.Fintech or insurtech background is a plus; familiarity with regulated environments and high-accuracy data requirements is a bonus.How We WorkIn-office in New York City, 4+ days a week (relocation covered). Building in person is how the team moves. Working hard and working sustainably aren’t in tension. Teammates regularly work from abroad and take time to stay at their best.Low process, high context, flat by design. The team organizes around the belief that category-defining companies are built by engineers with a hunger to own outcomes of increasing scope.Autonomy by default. The best engineering cultures run on intrinsic motivation, not management. The team hires people they don’t have to manage and gives them room to operate.Best idea wins. They want engineers who generate sharp ideas, defend them well, update fast when evidence moves, and stay obsessed with ground truth.CompensationCompetitive base aligned with experience (Series A/B startup engineer level).Significant founding-team equity, top of band.100% health insurance covered; technology package provided.Why NowCommercial insurance is a multi-trillion-dollar market still running on opaque pricing, fragmented data, and manual workflows. The inputs to fix it (modern data access, scalable infrastructure, AI that can reason over documents) just converged. No infrastructure layer has emerged yet. This creates a unique window to rebuild insurance into something transparent, data-driven, and software-native, and to define what it becomes.