Forward Deployed Engineer, Data De-Identification

Job Description:

• Own delivery of client de-identification projects from raw data through client acceptance
• Run corpora through the de-identification pipeline and check output accuracy
• Diagnose, explain, and fix pipeline problems
• Rerun pipelines and work with the annotation team to validate quality
• Build and adjust ingestion and transformation steps for mailboxes, chat archives, documents, ticketing systems, and databases
• Write code merged into the existing platform, including client-specific handling
• Run reconciliation checks from ingest through delivery
• Contribute to technical client reports covering sensitive data treatment, file handling, and limitations
• Walk clients through the work and resulting data
• Convert one-off fixes into reusable documentation, runbooks, and product improvements
• Learn the platform and delivery process, then independently run engagements from scoping to delivery

Requirements:

• A bachelor’s degree in a technical field (computer science, engineering, math, statistics, physics or similar)
• Several years of hands-on work in data engineering, backend engineering, or a solutions/forward-deployed role where you shipped production systems for customers
• Strong Python and SQL
• Comfortable reading and debugging other people's code
• Real experience with at least one major cloud (AWS, GCP or Azure): storage, compute, IAM, networking, and security controls
• Experience processing large volumes of unstructured and semi-structured data
• Record of delivering complex projects on short timelines, measured in days and weeks
• Clear communication with technical and executive audiences
• Self-direction and ability to make sound calls independently
• Daily use of AI coding tools, agents and LLMs
• Experience with model inference or ML pipelines
• Exposure to processing unstructured or semi-structured data
• Interest in working close to frontier AI labs and the training-data ecosystem
• Experience at an early-stage company or on a new product line

Benefits:

• Equity
• Bonus
• Competitive compensation
• Work alongside technical founders
• Exposure to frontier AI labs and the training-data market