Backend Engineer (AI Data Infrastructure Startup)

A fast-scaling startup supplies real enterprise data to AI research labs and other model builders, and it needs backend engineers to take charge of the pipeline that makes that data safe and usable. The engineering group is small, so each person carries a lot of ownership and influence over how the team works.

Your focus

Build and grow staged pipelines that process very large volumes and remove personal identifiers from confidential corporate data such as chat exports, email, documents, code repositories and project trackers, turning it into training-ready sets

Own backend services from design through shipping, debugging and correctness checks, so quiet failures, repeated records and outdated data never reach a customer

Make reruns, checkpoints, partial failures, backfills and rollbacks predictable and easy to understand across async orchestration, batch workers, message queues and object stores

Create in-house tools and dashboards that reveal how pipelines perform and where data quality slips, with queryable lineage behind go or no-go release calls

Partner with colleagues in ML, product, platform and security as new data types arrive

What you bring

Three to ten years as a software engineer who has personally owned production backend systems

Strong grounding in distributed and asynchronous design: queues, concurrency, idempotency and recovery

Experience with code that operates on the data itself, not just moves it between systems

Fluency in a general-purpose backend language; the stack is Python on AWS, though Go, Rust or Java engineers are welcome

Meaningful time at an early-stage or high-growth startup

A STEM degree from a leading university

Orchestration or batch workflow experience is a plus

On-site in New York, NY. Visa transfers considered.