Member of Technical Staff, Platform

About the Company

An early-stage AI company that places engineers directly inside enterprises and frontier AI labs to automate complex, real-world workflows, starting with engineering and life sciences. The company works with mid-market enterprises generating more than $50M in revenue, and partners directly with several of the leading AI labs, using what it learns in the field to build the evaluation data and environments that improve frontier models. Backed by a well-known early-stage venture fund and notable angel investors, the company is already at a significant run rate and growing fast, with the team roughly doubling in size by year end.

About the Role

The platform team builds the systems that make the company's core motion possible: how agents run, how experts review their work, and how results feed future datasets and deployments. The work spans distributed systems, data pipelines, and performance optimization, plus the internal tools experts use to write and review tasks. Agent runs can take hours and depend on model APIs, remote environments, and background services, so the job is to make those workflows reliable, help the team understand failures, and keep performance up as usage grows toward a goal of supporting trillions of tokens of processing per week. Sandbox infrastructure reliability is a live pain point right now. The team is leaning toward someone with genuinely high engineering standards (startups often hand-wave good infra practices; this team wants real standards instead), or a strong alternative: someone very early at a now-grown startup who personally stood up and scaled its infrastructure.

What You'll Own

• Long-horizon agent workflows, with a goal of supporting trillions of tokens of processing per week
• Services and data pipelines for task execution, evaluation results, and dataset delivery
• Investigating production issues, improving performance and resource usage, and building recovery from failure
• Reliability of agent runs that span hours and depend on APIs, remote environments, and background services
• Internal tools that experts use to write and review tasks, reducing repetitive manual work
  
  

What We're Looking For

• 3 to 7 years of professional experience
• Production software experience with a strong grounding in distributed systems, data pipelines, or performance optimization
• Sound engineering judgment: the ability to investigate unfamiliar problems across a codebase without needing them fully defined for you
• A track record of taking a project from requirement through implementation and release
• High engineering standards, ideally from an exceptional team, or real experience standing up and scaling infrastructure very early at a startup that then grew
• Brand-name or high-caliber-team signal, and demonstrated agency through side projects or similar
• Bonus: experience with agent workflows, model inference, or evaluation systems (a plus here, not a requirement)
  
  

Logistics

San Francisco, in office, with an intense pace (9-9-6). Compensation is $200K to $400K base plus 0.1% to 0.5% equity. Visa sponsorship is limited.