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Backend engineer role building the pipeline that de-identifies sensitive enterprise data, with ownership of versioned manifests, artifact contracts, lineage, state transitions, retries, checkpoints, replay, and backfills. Work includes independent reconciliation and verification of output, plus diagnosing production issues across queues, stores, and file formats. Stack includes asynchronous orchestration, batch workers, queues, object storage, and databases, with AI tools used in development and bounded verification.
We are building the first-ever bank for enterprise data. There are over 35 million businesses in the US alone, many of which are sitting on an asset they don’t know they have. At Replay, we help businesses monetize their historical operating data by licensing it to the frontier AI and data labs for model training. Replay sits at the intersection of advancing the frontier of AI, while helping companies generate millions in growth capital without having to give up equity, take on debt, or lay off employees.
We're hiring a backend engineer to make the pipeline that de-identifies sensitive enterprise data correct, replayable, operable, and safe to change.
This is not a conventional data-platform role where a successful job is enough. A pipeline can finish while silently dropping records, duplicating output, applying stale policy, losing lineage, or producing evidence that cannot establish whether a dataset is safe to release. You will own the backend systems and contracts that make those failure modes visible, preventable, and recoverable.
You will work across asynchronous orchestration, batch workers, queues, object storage, databases, many file formats, model-backed stages, deterministic verification, and human review. The role is backend-focused, but the outcome is a product and delivery promise: the team must know what ran, what changed, what remains uncertain, and what can safely happen next.
Compensation: $200K
