AfterQuery — Strategic Projects Lead - Coding

After Query — Strategic Projects Lead - Coding

Type: Full-time | On-site | San Francisco, CA
Compensation: $130,000–$150,000 base (up to $300K total cash comp) + competitive equity
Hiring count: 4
Visa sponsorship: None available
Reports to: Founding team (specific manager not stated)

After Query builds the training data and evaluation infrastructure that frontier AI labs use to improve their models, working with all five of the world's leading AI labs to design high-signal datasets and run rigorous evaluations that go beyond static benchmarks. One of the fastest-growing companies in its YC batch, backed by Y Combinator, Box Group, Lightspeed, Warburg Pincus, Silver Lake, and Index Ventures, with $30M raised at a $300M valuation.

Founded: 2025 | Team size: 11–50 | Total funding: $30M (at $300M valuation)
Industry: AI training data & model evaluation infrastructure

Website:  Office:
San Francisco, CA

• Direct founder access: Work directly with the founding team on their highest-priority, most ambiguous problems.
• Frontier lab exposure: Interface with research leads at the top AI labs; your work powers $10M+ contracts.
• Upside: Up to $300K total cash comp plus meaningful equity in a fast-scaling, venture-backed company.

• No separate intake call summary was present on the role page (intake video not transcribed here). If an intake transcript is available, add its key points here.

A founding-level role at the intersection of technical execution and strategic leadership — owning high-impact initiatives end-to-end while managing technical experts and shipping production code yourself.

• Own end-to-end technical initiatives: scoping requirements, building solutions, managing experts through delivery, and shipping code yourself when it unblocks the team.
• Design and build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines supporting multiple concurrent frontier lab contracts.
• Manage and mentor teams of software engineers, data scientists, and ML specialists on high-priority campaigns; set technical direction and hold the bar for execution velocity.
• Interface directly with research teams at leading AI labs to understand their needs, translate them into technical specs, and ensure delivery meets their standards.
• Debug production issues live under pressure; rapidly context-switch between hands‑on engineering, team leadership, and strategic problem‑solving.
• Support the founding team on whatever moves the needle most — internal tooling, closing technical details on major contracts, or hiring the next engineers.

Tech stack: Python; data pipelines, APIs, ML/AI tooling

• CS degree, engineering experience, or equivalent demonstrated ability to ship technical projects
• Manage teams of technical experts across software engineering, data science, and machine learning
• Build technical infrastructure and tooling for dataset generation, quality control, and delivery pipelines
• Drive technical and operational initiatives end-to-end: scoping requirements, building solutions, and managing technical experts
• Interface directly with engineering and research teams at leading AI labs
• Support founding team on high-priority technical projects and operational initiatives
• Proficiency in Python and production-quality code
• Experience with data pipelines, APIs, or ML/AI tooling
• Strong leadership experience and communication skills
• Ability to context-switch rapidly between technical and strategic work
• Intense work ethic, agency, and drive
• Competitive nature and track record of exceptional achievement
• Undergraduate degree from the U.S., Canada, or the U.K.

• Background in software engineering, ML engineering, AI research, or computer science
• Experience at top tech company (FAANG, frontier AI lab) or quantitative trading firm
• Prior startup experience or founding experience
• Willingness to work long hours and weekends when projects demand it

• Worked cushy tech jobs (FAANG PM, etc.) and may not be used to intense work environments.
• Struggles with ambiguity or lacks examples of owning large, complex projects.
• Only…