Forward Deployed AI Engineer

This is a hands-on, customer-facing engineering role at the intersection of AI, product, and implementation. You'll work directly with some of the largest insurance brokerages in the country, understanding their workflows, building AI automations on the company's platform, and shipping solutions within days, not months. The role is ~70% coding and ~30% customer-facing scoping. You'll hop on a call with a customer to understand their problem, then build and deploy an agent that solves it, often in the same week. Everything you build feeds back into the platform, so your work scales beyond a single customer. You won't be doing pre-sales, demos, or upselling: deployment strategists handle that. Your job is to deeply understand the business domain and build. This role is ideal for engineers who thrive at the intersection of customer empathy and technical execution, and who want to work on cutting-edge AI agents transforming a $1.5 trillion industry that hasn't seen real technology in 20 years. What You Will Do Own end-to-end implementation of enterprise customer engagements, from requirements gathering to deployed solution Build and ship AI agents and automations on the company's platform, deepening adoption within our largest strategic accounts Work directly with enterprise customers (post-sales) to understand business problems and scope technical solutions Ship rapidly: expect to deliver working solutions within the same week as customer conversations Integrate successful customer-specific work back into the core platform Collaborate with product and engineering teams to translate customer insights into scalable features

- 3-6 years of post-college engineering experience, no new grads - Customer-facing engineering experience on the post-sales side: scoping problems, building solutions, and shipping within the same week - Full-stack proficiency: comfortable shipping across front end and back end - Experience at a VC-backed startup (Series A+) funded by top-tier VCs - Degree from a top university (Ivies, Stanford, MIT, Berkeley, Duke, Harvey Mudd, Claremont McKenna, UIUC, or equivalent) strongly preferred - Strong ownership mentality: you don't wait for process, you create it - Proficient in Python and/or TypeScript - Experience building or deploying AI/ML automations or agentic workflows in a production environment - Experience building or integrating LLM/AI automation pipelines (e.g. OpenAI, LangChain, or similar) - Experience scaling enterprise deployments: building and shipping multiple product features or automations for large customers - Comfortable context-switching between customer-facing communication and heads-down coding - On-site 5 days/week in San Francisco