Senior AI Engineer - Agent Team

FurtherAI•San Francisco, CA

9d•Onsite

About The Position

At FurtherAI, we’re building the next generation of AI agents for the insurance industry - a trillion-dollar market ready for transformation. We’ve raised more than $30M from top investors (Andreesen Horowitz, YC, Nexus, South Park Commons, Converge) and have grown 10x in revenue this year alone. Our customers include some of the largest names in insurance (we recently closed a top 5 insurance company in the world), and our team combines deep AI expertise with proven company-building experience. Now, we’re looking for an exceptional AI Engineer to join our agent team and help shape both our product. Why Join Us Rocketship Growth: Post-PMF, with revenue growing at an exceptional pace. Elite Team: Team includes ex-Apple AI Research, 4 YC founders, and 6 ex-founders. Engineers have prior experience at Apple, Microsoft, Google, and Amazon. Massive Market Impact: Insurance is the backbone of global commerce - our work reshapes how this industry operates. Founder’s Mindset: Perfect fit if you want to own big pieces of the product and possibly start your own company in the future. Note that this is not a model-training role - you’ll be building orchestration and reasoning systems on top of existing LLMs (think Claude-Code over Claude-Model). At FurtherAI, we set a high bar. We’re not looking for someone who just wants a job. We’re looking for someone who wants to build something transformative. If you thrive in environments where the pace is fast, expectations are high, and the rewards are outsized, you’ll love it here.

Requirements

Amazing ability to speak with LLMs - Occam's razor in prompting
Strong experience with Python
6+ years building in ML/AI.
Clear communicator - both in person and in writing.
Above all: drive, grit, and ownership. If you excel here, other requirements are secondary

Nice To Haves

background in B2B SaaS and 0 - 1 experience

Responsibilities

Set up end-to-end evals to measure & improve agent performance.
Experiment with new agentic techniques (e.g. multi-agent systems, reasoning-from-feedback, RFT, etc)
Build lightweight tools, servers, and orchestration layers (e.g. MCP servers) that enable agents to operate reliably in production
Stay on top of emerging research and blogs on LLM/AI agents and bring ideas into production experiments.