Research Technical Program Manager

AfterQuery is an applied research lab curating data solutions for foundation model development.

We serve every frontier AI lab with the mission of delivering the best data to power the best models. In doing so, we can make expertise that once took a lifetime to build available to anyone who needs it. Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve.

This is a rare opportunity to join a company at a defining moment in AI. Since raising our $30M Series A at a $300M valuation, AfterQuery has grown well over a $100M revenue run rate.

We're based in San Francisco and backed by leading investors including Altos Ventures, BoxGroup, and Y Combinator and angels from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, and Microsoft AI.

• Massive Opportunity:
  We are one of the fastest-growing YC companies in our batch, and we believe we can become one of the fastest-growing YC companies of all time.

• Founding Impact:
  You will own and architect core infrastructure systems that power our platform from the ground up.

• Equity & Growth:
  Competitive salary and meaningful equity. As we scale, you’ll have the opportunity to shape the engineering organization and lead major technical initiatives.

• Strong Team:
  Our founding team has experience from Citadel Securities, Meta, Google, Silver Lake, and Morgan Stanley — work alongside world-class engineers and researchers.

Your job is to make ambitious research programs move. You will own the execution of programs spanning post-training, enterprise post-training, fellowships, evaluation releases, and partner research. You will turn open-ended research goals into clear plans, keep researchers, engineers, SPLs and external partners aligned, and surface the decisions and blockers that matter. This is not a traditional project-management role. You must understand the technical work well enough to reason about experiments, datasets, evaluations, training pipelines, and research tradeoffs. Your impact will come from creating just enough structure for the team to run more programs, make better decisions, and ship high-quality work faster.

Own planning and execution across post-training, enterprise post-training, fellowship, and public evaluation programs.

Translate ambiguous research objectives into milestones, owners, dependencies, success criteria, and decision points.

Maintain a trustworthy view of program health, including experiment progress, risks, blockers, partner dependencies, and upcoming releases.

2-4 years project/program management experience

Experience leading complex technical programs across research, machine learning, engineering, or data organizations

Working knowledge of the LLM development lifecycle, including data creation, SFT, RL-based post-training, and evaluation

Strong communication and an ability to turn messy technical information into clear decisions and next steps