Design and build high-performance, reliable data infrastructure for the AI era. Develop systems for high-throughput data pipelines, vector database optimization, and low-latency retrieval APIs. Collaborate with the founding team to create a platform for other engineers to build upon.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Title: Founding Infrastructure Engineer (Systems)
Target: Masters/Bachelors with a passion for distributed systems, databases, and high-performance computing.
Location: San Francisco, CA | On-Site
Compensation: $155K - $250K | 0.6% - 1.8% Equity
Visa Sponsorship: Available
About Us
We are building the mission-critical data infrastructure for the AI era. Backed by Andreessen Horowitz (a16z), we are solving the massive data ingestion, processing, and retrieval challenges that prevent AI agents from being truly effective in enterprise settings. Our founding team includes early engineers from Databricks and Confluent.
The Role
You will be the architect of our data plane. Your challenge is to build systems that are both incredibly fast and supremely reliable. You will work on problems like high-throughput data pipelines, vector database optimization, low-latency retrieval APIs, and building a platform that other engineers can build upon with confidence.
Ideal Profile
- Completed a degree in Computer Science with a focus on systems.
- You think about performance, scalability, and reliability first. You are passionate about databases, concurrency, and networking.
- Strong proficiency in Go, Rust, Java, or C++ is required. Python is used but not the core language for this role.
- Experience or strong interest in distributed systems, Kubernetes, database internals, and cloud infrastructure (AWS/GCP).
- You enjoy reading the documentation of databases and infra tools to understand how they work under the hood.
- You might have contributed to open-source infrastructure projects or built your own database or orchestration tool for a project.
Apply if you're interested in: Distributed systems, database engines, vector similarity search, orchestration (K8s, Dagster), and building foundational platforms.