Forward Deployed Engineer, Data De-Identification

The role

You will own the delivery of client de-identification projects by running corpora through a de-identification pipeline. You will diagnose problems, build ingestion and transformation steps, and write code to handle client-specific data.

What you will do

• Own the delivery of client de-identification projects.
• Run corpora through the de-identification pipeline and check output accuracy.
• Diagnose and fix problems within the solution.
• Build and adjust ingestion and transformation steps for raw exports.
• Write code that gets merged into the existing platform.
• Run reconciliation checks for file counts and content.
• Contribute to technical sections of client reports.
• Walk clients through the process and resulting data.
• Turn one-off fixes into reusable documentation, runbooks, and product improvements.

Required qualifications

• A bachelor’s degree in a technical field (computer science, engineering, math, statistics, physics, bioinformatics, 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 experience in Python and other backend programming languages, plus SQL.
• Comfortable reading and debugging other people's code.
• Experience building repeatable pipelines that process large volumes of structured, semi-structured, and unstructured data.
• AI-native workflow.
• Self-direction.
• Clear communication with very different audiences.
• A record of delivering complex projects on short timelines.

Nice to have

• Experience with model inference, ML pipelines, or PyTorch.
• Experience building or maintaining data masking, de-identification, ETL or synthetic data tooling.
• 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

• Competitive compensation
• Equity

About the company

Tonic.ai has been de-identifying sensitive data since 2018. Hundreds of enterprises use their products to protect people in datasets used for training AI.