About the RoleJoin the platform team at a seed-stage AI-native analytics startup building an agentic data lakehouse that delivers trustworthy answers from complex enterprise data. You'll help shape the data foundation that powers AI-driven analytics at scale - without heavy schema migrations or data movement. This is a high-ownership role at the core of the product.
What You'll Do- Build the agentic semantic layer that gives agents the context to query enterprise data correctly and the guardrails to prove their results.
- Design and implement orchestration systems for distributed agents, including API integrations, rate limiting, OAuth passthrough, model routing, scheduling, and token optimization.
- Architect AI-centric ETL pipelines for data lakehouses that make large-scale analytics accessible to organizations with minimal data engineering resources.
What We're Looking For- 4+ years of experience as a backend or platform engineer building scalable distributed systems.
- Strong proficiency in Golang, with the ability to contribute across infrastructure, services, or frontend as needed.
- Hands-on experience with gRPC/ConnectRPC, Trino, Kubernetes, DuckDB, and PostgreSQL in a distributed data platform context.
- Experience building orchestration systems for distributed agents, including API integrations, rate limiting, OAuth, model routing, or token optimization.
- Experience designing or implementing ETL pipelines, data modeling, or schema design for data platforms.
- Background at early-stage, VC-backed startups with a track record of building products from zero to one.
- Strong CS fundamentals; bachelor's degree in Computer Science, Software Engineering, or equivalent professional experience.
- Familiarity with data visualization tools or big data technologies (e.g., Spark, Hadoop, or similar) is a plus.
Compensation & BenefitsSalary range:
$200,000 - $350,000 USD annually. Equity included. Visa sponsorship is available.
LocationOn-site in
New York, NY. Candidates must be willing to work in-office full time.
