Backend Engineer

Building the data platform behind our product: ingestion, normalization, and enrichment pipelines for catalogs of millions of SKUs across Postgres and BigQuery, with lineage back to every source.
Syncing customer systems of record: mirroring data from customer PIMs, ERPs, and ecommerce platforms into BigQuery, with history. It's millions of products and thousands of attributes.
Designing durable, long-running workflows: building research agents that run for hours across hundreds of LLM calls and recover cleanly when something fails.
Shipping APIs the product and customers depend on: versioned, multi-tenant APIs that power our web app and external integrations.
Owning infrastructure and on-call: keeping a data-intensive AI app fast, observable, and affordable. Includes the AI plumbing (caching, sandboxing, traces, evals) that lets us develop features with confidence.
Owning features end-to-end: shaping the idea, building an MVP, testing in production, and iterating. Backend-led, with frontend support when you need it.
Talking with and supporting customers: joining customer calls to ask questions and share early work, plus rotating into support.

Strong software engineering fundamentals: you take a system from idea to deployed and stable.
Significant backend experience: production APIs, services, and data pipelines.
Experience with data engineering at scale: warehouses, ETL or ELT, batch and streaming patterns.
Comfort with distributed systems primitives: queues, workers, idempotency, retries, eventual consistency.
Experience designing APIs that other engineers or customers rely on day to day.
Comfort with our stack (TypeScript, Postgres, BigQuery) or transferable experience in similar tools.
Comfort operating in ambiguity and taking initiative without perfect specs.
Strong writing skills: you can make a complex idea clear in a few sentences.

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