Senior Backend Engineer

Join a small engineering team at an AI data infrastructure company to build and operate backend systems that prepare sensitive enterprise data for AI training. You will help ensure high-volume data pipelines are reliable, auditable, and safe to recover when failures occur. What You’ll Do

• Build and scale multi-stage pipelines that de-identify enterprise data from communication, email, document, code, and project management sources.
• Own backend systems from design and delivery through debugging, correctness checks, and recovery.
• Make retries, checkpoints, partial failures, replay, backfills, and rollbacks safe across asynchronous workflows, batch workers, queues, and object storage.
• Build internal tools and dashboards to monitor pipeline performance, investigate data quality, and support release decisions with queryable provenance.
• Work with machine learning, full-stack, platform, and security teammates to support new data types and pipeline capabilities.

• 3 to 10 years of software engineering experience, including personal ownership of production backend systems.
• Experience building and operating high-volume data processing systems that transform data, not only move it between systems.
• Strong distributed and asynchronous systems fundamentals, including queues, workers, concurrency, idempotency, retries, and recovery from partial failures.
• Backend depth and strong experience in a general-purpose language such as Python, Go, Rust, or Java.
• Experience with AWS and batch or workflow orchestration. Relevant technologies include Airflow, AWS Batch, SQS, S3, DynamoDB, and PostgreSQL.
• Meaningful early-stage or high-growth startup experience, a STEM undergraduate degree, and a track record of ownership and progression.