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 Client’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 Client’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 Client’s core platform
• Collaborate with product and engineering teams to translate customer insights into scalable features

Customer-facing engineering experience on post-sales side scoping problems, building solutions, and shipping within the same week VC-backed startup pedigree , experience at a company that raised Series A+ from a top-tier VC Hard skills Proficient in Python and/or TypeScript Baseline Seniority 3 - 6 years of experience in software engineering, forward deployed, solutions, implementation or product engineering , role is ~70% coding (mix of customer-facing builds and platform work) and ~30% customer-facing scoping and requirements gathering Work experience Experience scaling enterprise deployments , building and shipping multiple product features or automations for large customers Education Degree from a top university , Ivies, Stanford, MIT, Berkeley, Duke, Harvey Mudd, Claremont McKenna, UIUC, or equivalent strongly preferred Soft skills Comfortable context-switching between customer-facing communication and heads-down coding Miscellaneous On-site 5 days/week in San Francisco Work experience Built or deployed AI/ML automations or agentic workflows in a production environment Hard skills Experience building or integrating LLM/AI automation pipelines (e.g. OpenAI, LangChain, or similar) Traits to avoid Candidates with only large-company experience, no startup exposure or software consulting backgrounds SWEs-turned-FDEs looking to return to pure SWE (no direct customer interaction experience) Job hoppers , 3+ jobs in 3 years for early-career candidates is a red flag International candidates without substantive US work experience, * 3-6 years of post-college engineering experience, no new grads

• Customer-facing engineering experience, comfortable interfacing with enterprise customers regularly
• 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, UIUC, or equivalent)
• Strong ownership mentality, you don’t wait for process, you create it

Bonus Qualifications

• Experience building or deploying AI/ML automations or agentic workflows in production
• Proficiency in Python and/or TypeScript
• Experience in insurance or financial services domain

Why candidates should join

• Rocket-ship traction. Client hit multiple seven figures in ARR in just over a year and already serves 30% of the top 50 insurance brokers in the country.
• Fresh $25M Series A. Backed by CRV, South Park Commons and Foundation Capital , strong institutional names with deep enterprise software conviction.
• Extreme ownership from day one. You work directly with enterprise customers and ship end-to-end AI automations that show up immediately in their workflows , no bureaucracy, no hand-holding.
• Top-of-market comp. $180K-$300K base plus meaningful founding-team equity at a 30-person company that’s just getting started.
• Staff-level team pedigree. You’re joining ex-Affirm, Uber, DoorDash and McKinsey operators in-person in San Francisco , the kind of team that moves fast and builds things that matter.