Working with our core engineering team, you’ll be critical in creating data infrastructure that will be shaping the future development of frontier models. You will get a lot of responsibility, owning entire projects end-to-end – meaning you can see your impact instantly.
Company Overview
AfterQuery is a research lab investigating the boundaries and capabilities of artificial intelligence through novel datasets and experimentation. Our customers are the foundation model labs, and we serve all of the frontier AI labs.
We are based in San Francisco, CA, and have raised funding from top investors, including Y Combinator and BoxGroup, ex-partners from Lightspeed and Index Ventures, and senior leadership at Google DeepMind and Meta GenAI.
Our founding team brings backgrounds from Jane Street, Meta, Citadel Securities, Google, Goldman Sachs, Morgan Stanley, Silver Lake, Berkeley Artificial Intelligence Research (BAIR), and Stanford Artificial Intelligence Laboratory (SAIL).
Why Apply
- Massive Opportunity: We were one of the fastest growing YC companies in our batch, and we believe we can be one of the fastest growing YC companies of all time
- Founding role—you’ll define and own our data infrastructure from day one.
- Strong Team: Founding team has experience from Citadel Securities, Meta, Google, Silver Lake, and Morgan Stanley – get to work with the best :)
Responsibilities
- Build and scale complex data capturing workflows across web (Next.js) and desktop (Python)
- Architect and optimize data pipelines that experience high throughput, with heavy loads
- Collaborate with the founding team to define product strategy and ship features fast.
- Set engineering best practices and lay the groundwork for future team growth.
Required Qualifications
- Able to take a gap semester off and join our team in person in San Francisco
- Proficiency in JavaScript (Next.js) and Python, with demonstrated experience building full-stack web applications
- Experience with serverless architecture and cloud functions for implementing heavy data processing (GCP/AWS)
- Storage, caching & search: Hands‑on with Redis (caching), Elasticsearch (indexing), and message queues (Kafka/RabbitMQ) to build scalable, low‑latency pipelines.
- Any background in AI research, LLM evaluation, or human‑in‑the‑loop systems
- Experience getting your ideas into production (founder experience preferred)
