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Mercor is an AI data company building infrastructure between human expertise and frontier AI models. The company operates a network of domain experts who train AI systems, and is expanding into enterprise with Mercor Enterprise, helping Fortune 500 companies capture and operationalize how their best people work.
You'll join the Frontier Data Products team to build core production systems that capture, coordinate, and validate expert judgment and high-quality data workflows at scale. This is a backend systems and orchestration challenge: frontier AI companies are increasingly bottlenecked on expert judgment, and you'll build the distributed state machines that handle multi-stage workflows combining automated processing, model inference, and expert review.
The technical problem is novel: these are long-running, stateful systems where a single job can stay live for days, interleaving automated steps, model calls, and human review. State can be reopened and redone after marking "done," so correctness must survive humans and models disagreeing with each other. You'll design services and state models for workflows that fan out and reconcile results, build orchestration primitives (retries, failure recovery, idempotency, auditable transitions), integrate model inference without sacrificing debuggability, and own reliability and observability end-to-end.
You'll work closely with product, operations, and ML teams to translate constraints into clean system design. The architecture is not yet set—early engineers decide what it becomes, and the feedback loop between shipping and impact is short. You'll own your systems end-to-end: design, ship, operate, improve.
Mercor is a profitable Series C company valued at $10 billion, requiring in-person work five days a week at San Francisco, NYC, or London offices. The role requires production backend experience, strong system design instincts, fluency with distributed systems (async workflows, queues, idempotency, retries, long-running jobs), and comfort with Python on AWS and Postgres. Experience with Temporal or similar workflow engines is a plus.
