Company Overview
Most companies don’t end in acquisition — they end in closure. Yet shutdown has never been given the same rigor, clarity, or professionalism as the moments that came before it. Nearly 4 million companies shut down every year, creating a massive, overlooked market. SimpleClosure is building the infrastructure to change that.
Having raised over $20M from leading VCs and trusted by more than 7,000 companies to date, we streamline the entire business dissolution process — from legal and tax to operational and administrative — as one coordinated effort instead of a patchwork of disconnected steps. We go a step further, helping companies sell their remaining assets and return the most value to their stakeholders, through our Asset Hub.
As the leading platform for company shutdowns, we have something no one else does: a continuous, proprietary flow of companies winding down, and the assets they built along the way. Our buyers span the top AI labs, RL environment providers, vertical and enterprise agent builders, VCs and deal-flow partners, domain marketplaces, and much more. Dissolution is our wedge; the marketplace is a big part of where we’re headed.
Joining our Asset Hub team means helping to define a new category from the ground up, working on complex, high-stakes problems, and building the products and processes that guide founders through one of the most consequential moments in a company’s life.
Job Overview
SimpleClosure 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, base and variable
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
SimpleClosure is an equal opportunity employer
We are committed to providing a work environment free of discrimination and harassment. All employment decisions at SimpleClosure — including recruiting, hiring, promotion, compensation, and termination — are based on qualifications, merit, and business need, without regard to race, color, religion, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. We’re committed to building a diverse and inclusive team, and we welcome applicants from all backgrounds. If you need a reasonable accommodation during the application or interview process, please let us know.
Application Process
Thanks 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.