Software Engineer

I’m working with a fast-growing AI company building the expert reasoning and data infrastructure used by frontier AI labs to improve their models.

They capture the step-by-step reasoning, judgment and decision-making of verified domain experts and turn it into high-quality training data, evaluation environments, agent trajectories and RL infrastructure.

The company has scaled at an exceptional pace; reportedly becoming YC’s fastest unicorn ever after raising at a $3.2B valuation, around 10x its previous valuation in just five months. It is backed by leading venture investors and already generates significant revenue while operating with a lean, high-caliber engineering team.

This is a high-ownership role for someone who wants to build core platform infrastructure from the ground up in a fast-moving environment.

You’ll work on:

• Architecting and scaling high-throughput data pipelines
• Building complex data-capture workflows across web and desktop
• Designing backend and platform infrastructure in Python
• Working with distributed systems, queues, caching and search infrastructure
• Building production systems across cloud environments
• Owning projects end-to-end from architecture through deployment
• Working directly with the founding team to define technical direction and ship quickly

• Candidates from highly selective startups, quantitative engineering environments or similarly demanding technical teams are especially relevant
• Strong backend, platform or infrastructure engineering experience
• Strong Python experience, ideally with some full-stack capability
• Experience building scalable production systems or high-throughput data infrastructure
• Strong cloud and distributed systems fundamentals
• Evidence of personally owning and shipping substantial systems into production
• High agency and comfort operating in a fast-moving, low-process environment
• Exceptional academic and technical pedigree. The hiring bar is very high, with a strong preference for top computer science backgrounds
• Experience in AI infrastructure, LLM evaluation, human-in-the-loop systems or applied AI is highly valuable