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.
Why ApplyMassive Opportunity:
We were 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.
Project and client management: Partner directly with frontier AI labs on their legal data and evaluation needs — scoping the problem, translating it into a deliverable program, and driving revenue.
Manage expert contractor teams: Recruit and lead practicing attorneys and specialists across practice areas and jurisdictions — litigation, corporate and M&A, regulatory, IP, tax, employment — and hold a high bar on the quality of what they produce.
Shape AI training: Design the specifications behind legal reasoning datasets, contract and document review tasks, statutory and case-law interpretation problems, multi-step research workflows, and the rubrics used to grade them.
Define what "correct" means: Build the grading standards and evaluation criteria that let a lab distinguish real legal reasoning from confident-sounding error, including citation integrity and jurisdictional accuracy.
End-to-end execution: Own projects from scoping through final delivery, in a fast-moving environment where the spec often does not exist yet.
Operational impact: Support initiatives across building, analysis, coordination, and
3+ years practicing law at a leading firm, in-house at a sophisticated company, a government or regulatory body, or a legal AI startup.
JD (or equivalent qualification) and a track record of substantive legal work: you have drafted, negotiated, litigated, or advised, not just coordinated.
Deep command of legal reasoning and research methodology, and strong opinions about what separates rigorous analysis from surface-level answers.
High agency and the ability to execute in ambiguity; comfort defining the problem before solving it.
Analytical ability; can break down complex legal problems and work flows into component parts.
Genuine passion for AI and interest in entrepreneurship.
Demonstrated track record of competitive success.
Strong leadership and communication skills.
Comfort with data and AI tools.
Python proficiency or hands-on experience with data analysis.
Experience with legal technology, e-discovery, contract analytics, or AI-assisted legal workflows.
Depth in a technically demanding practice area (securities, antitrust, tax, patent prosecution, complex regulatory).
Multi-jurisdictional or non-US legal experience.
Experience using AI tools to automate workflows and build products.