Founding engineer — data & ai

Sieora is a fast-growing AI outbound company. We run revenue operations for our clients, and we're building the data platform underneath it.

You'd be the first engineer, and you'd own it end-to-end.

THE WORK Pulling large volumes of historical data out of third-party Saa S APIs — full multi-year backfills rather than live streams. Pagination, rate limits, resumable jobs, partial failure. A Postgres model where time is first class: when something happened, and when we learned it, tracked separately. Language models over large volumes of unstructured text — structured extraction, confidence scoring, and keeping the cost sane at volume. Detection logic over the resulting dataset, and the reporting on top of it. Agents that act on the output, with human approval gates. WHAT WE NEED Strong Python. Postgres you've designed rather than inherited — schemas, indexes, migrations. You've built an integration against somebody else's API with pagination, rate limits and a resume-after-failure path. Ideally a large historical backfill. You've shipped an LLM feature to production where the output was acted on, not just shown to a user — and you can talk about how you knew it was good enough. You've shipped something alone, including deploying and running it. WHAT WOULD MAKE YOU UNUSUALLY GOOD AT THIS You've modelled time properly before — event sourcing, audit trails, temporal or bi-temporal data, slowly-changing dimensions. You've worked with CRM or marketing platform APIs. You're comfortable being the only engineer, and you'll tell a non-technical founder when he's asking for the wrong thing. WHAT'S ALREADY RUNNING

Paying clients, real revenue, campaign automation, enrichment and the outbound engine. This is a product being built inside a business that works, not a pre-revenue idea.

STACK

Python, Postgres, Claude, third-party Saa S APIs, and some Next.js where a front end is needed. #J-18808-Ljbffr