Principal Engineer

Principal Engineer

Vouch is the insurance broker that powers ambition. We're a tech-enabled insurance advisory and brokerage purpose-built for growing companies in technology, life sciences, and professional services. Our clients are ambitious leaders building complex businesses, and we help them manage risk with tailored advice, smart coverage, and responsive service.

Backed by over $200M from world-class investors, Vouch combines deep industry expertise with AI-powered tools to deliver a better insurance experience. Our digital workflows reduce friction, speed up decisions, and give our clients the confidence to move faster.

Vouch has employees located across the U.S., with offices in San Francisco, Chicago, and New York City. This role will be aligned to our Chicago office. While this role has hybrid work flexibility, we require team members to be in the office at least three days per week (Tuesday, Wednesday and Thursday) to foster close collaboration and team building.

This is a principal-level individual contributor seat reporting directly to the CTO, with a mandate that spans our estate: a harness for agent-built software — your first ownership deliverable — production AI doing judgment-heavy insurance work, a backend whose bounded contexts need to become real, and the cloud platform underneath all of it.

What You'll Do:

• Own the platform that governs agent-built software. A harness where markdown specifications compile to a traceability lock, deterministic gates decide "done," every agent action leaves tamper-evident evidence, and a calibrated multi-vendor panel of LLM reviewers blocks what humans should not have to catch. You will take it from working extraction to adopted platform: scope its next milestone, build its plugin surface, operate and score the review seats, and prove it generalizes beyond the repository it was born in.
• Make bounded contexts real across our backend. Our backend estate asserts "one service = one bounded context"; a handful of services actually implement ports and adapters; the rest is your brownfield. You will turn design-doc DDD into enforced architecture — context maps, anti-corruption layers, boundary checks that run in CI — without freezing a team that ships daily.
• Ship agentic systems that do real insurance work. Durable multi-week agent workflows with human approval gates, tool contracts and capability boundaries, planner/executor orchestration — extended in production, in front of the experts whose judgment they encode.
• Make model behavior measurable — and autonomy earned. Eval suites as merge gates, golden datasets, LLM tracing and token/cost observability, calibration of LLM reviewers against ground truth. Autonomy expands when the evidence says so, and you own the evidence.
• Run platform and delivery engineering at organization scale. An AWS multi-account estate in Terraform behind Git Ops; two orchestrators in production; CI/CD pipelines that are generated, not hand-written; ephemeral environments per pull request. You will make the paved road faster than the shortcut.
• Be the CTO's architecture thought partner — and raise the bar. Strategic-design working sessions, ADRs with teeth, review comments that catch what tests cannot; specifications written to be read by humans and coding agents alike, mutation-testing bars, adversarial review. When we argue about where a boundary belongs, you are the other half of the argument.

About You:

A principal engineer here is equal parts AI engineer, Dev Ops engineer, and software architect. We mean that literally, and we will interview for all three.

You are a software architect.

• You have shipped domain-driven design, not just read about it: a bounded-context map you drew and then enforced, an anti-corruption layer that saved a migration, a hexagonal refactor that survived contact with a deadline — and you know when the pattern is overkill.
• You are at home in more than one language ecosystem — e.g., systems-level work in Rust or a peer language, large-scale strictly-typed Type Script, etc. — and you know which discipline each one demands.

You are an AI engineer.

• You have built and operated agent systems in front of real users —…