YC-backed startup developing agent-based systems that automate quantitative research and trading, with a founding infrastructure engineer role offering $150-200K and 1-3% equity.
Event Horizon Labs is building what they call "AI-native" quantitative research infrastructure—systems where autonomous agents generate trading hypotheses, backtest strategies, and analyze results without human intervention. The San Francisco-based startup, part of Y Combinator's W24 batch, has developed a platform where hundreds of agents run in parallel, learning from each other's discoveries to compound knowledge over time.
The company's approach represents a fundamental shift in how quantitative research gets done. Rather than having teams of analysts manually testing trading strategies, their platform orchestrates autonomous research sessions that can scale with each new model release. The agents discover profitable strategies, analyze market data in real-time, and execute trades—all while maintaining observability and reproducibility at scale.
Founding Infrastructure Engineer Role
The company is hiring a Founding Infrastructure Engineer to build the platform that makes this all possible. This isn't a typical backend role—it's about designing distributed systems for autonomous AI agents. The position offers $150,000-$200,000 in salary plus 1-3% equity, reflecting the founding nature of the work.
Key responsibilities include building the orchestration layer that dispatches parallel research sessions, creating streaming data pipelines for real-time market ingestion, and designing low-latency trading systems. The tech stack centers on Python, Go, and Kubernetes, with a focus on streaming data and distributed systems.
Why Markets First?
Event Horizon Labs chose financial markets as their initial domain for specific reasons: feedback is immediate, signals are verifiable, and outcomes are directly monetizable. A trading strategy either makes money or it doesn't—there's no ambiguity. This clarity makes markets ideal for testing autonomous research systems.
The team comes from prestigious backgrounds including Citadel, Jump Trading, Stanford, Caltech, and Berkeley, bringing both trading expertise and technical depth to the challenge.
Beyond Trading
The company's vision extends beyond financial markets. They see their autonomous research infrastructure as a general-purpose platform for autonomous problem-solving. If agents can discover profitable trading strategies, similar approaches could tackle other complex domains where rapid feedback and verifiable outcomes exist.
The Infrastructure Challenge
Building systems for autonomous agents presents unique challenges compared to traditional software. The Founding Infrastructure Engineer will need to solve problems like:
- Compute scheduling and resource allocation across hundreds of concurrent agents
- Streaming data pipelines that can handle real-time market data at scale
- Agent observability to track what each autonomous researcher is doing
- Experiment tracking to ensure reproducibility of AI-generated strategies
- Low-latency trading systems that can act on discoveries within milliseconds
This represents a new category of infrastructure problem—distributed systems specifically designed to support autonomous AI agents rather than human users or traditional applications.
Company Stage
Founded in 2024 with a team of just four people, Event Horizon Labs is in the earliest stages of building what could become a new paradigm for quantitative research. The founding team includes Owen Colegrove, who is listed as founder. The company is actively hiring and based in San Francisco, with in-person work required.
The role represents a chance to shape the foundational architecture of AI-native quantitative research from the ground up, with significant equity upside and the backing of Y Combinator's network.
Comments
Please log in or register to join the discussion