Sign up free to see how well your resume matches this role.
Join 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.
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.
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.
Salary range: $200,000 – $350,000 USD annually. Equity included. Visa sponsorship is available.
On-site in New York, NY. Candidates must be willing to work in-office full time.
