Job OverviewSimpleClosure is seeking a Solutions Engineer, AI Data, to own how AssetHub's data gets from the companies that built it into the hands of the AI labs that buy it. When companies wind down, we acquire the real assets they built - production codebases, workspaces, and databases. You'll pull that data from sellers, shape it to each buyer's exact requirements, deliver it, and work with buyers to implement different feedback or fixes.
This is a hands-on, customer-facing engineering role that could be forward deployed in some instances. You'll work directly with research and data teams at frontier AI labs and with founders and engineers on the seller side, in a small, dedicated Asset Hub pod alongside product, engineering, BD, and the GM of Asset Hub.
*Candidates MUST be located in the New York City Metro area.
Key Responsibilities- Work with sellers and their engineers to extract codebases, workspace exports (Slack, Jira, Notion, Drive), and databases, and ingest them cleanly into our pipeline.
- Translate each buyer's requirements into custom scripts: transformations, filters, formats, and packaging tailored to how they train and evaluate models.
- Own technical delivery end to end: delivery specs, secure transfer, documentation, validation, and iteration until the buyer confirms the data is usable.
- Build and run evaluation scripts on codebases and workspaces (quality, completeness, size, training and RL signal), and help define how AssetHub scores and prices assets.
- Be the technical point of contact for lab data teams: join buyer calls, answer technical questions, scope custom requests, and feed what you learn into product and pricing.
- Turn one-off scripts into reusable tooling so every delivery is faster than the last.
- Handle sensitive material (codebases, workspace exports, and proprietary datasets) with strong attention to security, privacy, licensing, and PII handling.
Desired Skills & Qualifications- Experience: 2-5 years as a software, data, or ML engineer, ideally in a forward deployed, solutions, or other customer-facing engineering role.
- Core engineering: strong Python and SQL; fast, production-quality scripting and data pipelines; comfortable with messy real-world data.
- Evals: familiarity with how LLMs are trained and evaluated, including pretraining vs. SFT vs. RL data, evals, agent harnesses, and RL environments.
- Ownership: takes delivery from first request to accepted dataset, works scrappily, and thrives in ambiguity.
- Communication: credible with a lab researcher in the morning and a seller's founder in the afternoon.
- Education: Bachelor's or Master's in Computer Science or a related field, or equivalent practical experience.
- Nice to have - AI-data / evaluation background: experience at an AI data vendor (e.g. Scale, Surge, Snorkel, Mercor, Handshake AI, Turing) or on a lab's data team, or hands-on work producing training or evaluation data for models. Data licensing or compliance exposure; contributions to public benchmarks or eval frameworks.
What we offer- Compensation: $140,000 to $170,000
- Comprehensive health benefits, including medical, dental, and vision
- Life insurance
- Unlimited paid time off
- Flexible hybrid work environment in New York City, Midtown (currently 2 days per week in office)
- Two company-wide offsites each year
- 401(k) with Traditional and Roth options, with immediate eligibility
Application ProcessThanks for applying! If your experience is a strong match for what we're looking for, our hiring team will reach out to schedule an initial screening call and walk you through the rest of our interview process. We do our best to respond to every applicant, but given the volume of applications we receive, we may not be able to provide individual updates if we decide not to move forward.
