--- title: 'Legal Operations Lead at HUD' canonical: 'https://feeny.ai/job/legal-operations-lead-hud-san-francisco-r3g81avd0wqm' type: 'job' last_seen: '2026-09-15' --- # Legal Operations Lead at HUD - **Company:** HUD - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-09-02 - **Last confirmed live:** 2026-09-15 - **Apply:** https://jobs.ashbyhq.com/hud/e31e5ee4-48fc-4fdb-8fdb-fda953b7b304 ## Job description ## About HUD [HUD](https://www.hud.ai/) is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25. ## About the role We’re looking for a Legal Operations Lead to build and own the systems, processes, and commercial frameworks enable HUD to move more quickly as our volume and complexity of agreements grows. This is not a traditional in-house counsel role. We’re looking for someone who combines strong legal and contracting judgment with an operator’s instinct for systems, tooling, and leverage. You should be comfortable handling a contract directly one day and redesigning the process so it barely needs manual intervention the next. ## Responsibilities - Own the end-to-end operating system for legal at HUD, including intake, prioritization, contracting workflows, approvals, escalation paths, document management, and outside-counsel coordination - Draft, review, and negotiate routine commercial agreements across buyers, data vendors, and other partners, including MSAs, SOWs, data licenses, SLAs, NDAs, vendor agreements, and other bespoke arrangements - Build and continuously improve templates and negotiation playbooks so recurring issues such as data rights and usage restrictions can be handled quickly and consistently - Identify opportunities to automate or streamline high-volume legal workflows using software and AI, while preserving appropriate human review for judgment-heavy issues - Establish clear rules for what should be handled internally, what can be standardized or automated, and what should be escalated to founders or outside counsel - Manage outside counsel strategically, including scoping work, preparing issues efficiently, controlling legal spend, and ensuring external lawyers are used primarily for high-value or specialist questions ## Experience You may be a good fit if you have: - Experience in legal operations, contracts management, commercial operations, transactional legal work, business operations, or a combination of these at a fast-growing technology company - Strong experience drafting, reviewing, and negotiating commercial technology agreements, with the judgment to distinguish routine issues from matters that require specialist legal advice - Comfort working with legal technology, workflow tools, and AI, and an interest in using them to make legal work materially faster and more scalable - Strong commercial judgment and the ability to balance legal risk against speed, customer needs, and business priorities - Excellent written communication, attention to detail, and the confidence to push back constructively on sophisticated customers, vendors, and internal stakeholders Strong candidates may also have: - Legal training, including experience at a law firm or in-house legal team, but prefer operating and building systems over practicing law as a traditional counsel - Experience building or scaling legal operations, contract management, or a deal desk from an early stage - Experience with data licensing, IP-intensive transactions, marketplaces, or other businesses where contractual rights are closely tied to the product - Experience managing outside counsel - Early-stage startup experience with ability to work independently in fast-paced environments We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria. ## Team & company details - Team Size: ~25 people currently, mostly full-time in-person, but some remote. - Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. - Company stage: We have 8 figures in funding and high revenue growth. We’re scaling profitably and quickly to meet very strong demand. Logistics - Employment: Full-time. - Location: On-site only, for now. You can join the team in the San Francisco Bay Area or Singapore offices. - Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US or Singapore. - Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial. ## What we offer - Competitive compensation - 100% covered top-of-the-line medical, dental, and vision from Blue Shield of CA (US employees) - Lunch and dinner when you’re in the office - Company-wide holiday break (Christmas Eve to New Year’s Day) on top of PTO and paid holidays - Other perks including an Equinox membership, 401k, and commuter benefits (US employees) - Unlimited* access to tokens for ChatGPT, Claude Code, Cursor, etc. *By unlimited, we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is. Due to high volume, we may not actively respond to every application, but feel free to contact us at recruiting@hud.so or elsewhere if we missed your application! ## About HUD ## Company Overview - **One-liner**: HUD (Human Union Data, Inc.) provides the first comprehensive evaluation platform for Computer Use Agents (CUAs), enabling frontier AI labs to build reinforcement learning environments and run detailed evals for AI agents that browse the web. - **Entity Type**: Private (YC W25 startup; raised $500K in Pre-Seed funding led by Y Combinator) - **Headquarters**: San Francisco, California, United States - **Founded**: 2025 - **Founders**: Jay Ram (CEO), Parth Patel (CTO) ## Core Business - **Primary industry**: AI infrastructure – evaluation and reinforcement learning environments for browser‑based AI agents. - **Target customers**: Frontier AI labs (B2B), researchers building computer‑use and browser‑use agents. - **Mission / Purpose**: Provide the infrastructure to make AI agents work reliably in the real world by enabling detailed evals across thousands of tasks. ## Products & Services - **[CUA Evals Platform](https://www.hud.so/)**: An all‑in‑one platform for evaluating computer‑use and browser‑use AI agents. Supports 40+ models (GPT, Kimi, Qwen, etc.) and includes hundreds of environments and thousands of tasks. Used to generate both evaluation results and training data for reinforcement learning. ## Market Standing - **Valuation**: $3.3M (most recently disclosed, per Latka, Sep 2025) - **Key Metric**: $1.1M revenue (2025) – note: Latka reports the company as bootstrapped, but other sources (YC, LinkedIn) show $500K in outside funding; this may reflect different accounting or a conflict in data. - **Total Funding**: $500,000 (Pre-Seed, led by Y Combinator, with participation from several angel investors) - **Notable Investors / Partners**: Y Combinator (lead), backed by YC W25 batch; works closely with frontier AI labs. - **Growth Signals**: - Headcount grew ~150% YoY (from ~4 to ~9–15 employees). - Launched public beta in March 2026. - Active job postings increased 66.7% month‑over‑month. - Strong social engagement: LinkedIn followers grew 448.9% yearly. ## Competitive Advantages - First‑mover in a nascent category: HUD’s platform is described as the first comprehensive evaluation tool specifically for Computer Use Agents. - Tight integration with Y Combinator and frontier AI labs provides direct feedback and early‑adopter relationships. - Supports a wide range of models (40+) and can generate RL training data, not just eval results. ## Strategic Focus - Scale the platform to serve more frontier labs and researchers. - Expand the number of environments and tasks covered by evaluations. - Continue building out reinforcement learning infrastructure for agentic AI. ## Why Work Here - **Culture**: Small, ambitious team (≈15 people) backed by Y Combinator, focused on solving a cutting‑edge problem in AI reliability. - **Work Policy**: In‑office / in‑person in San Francisco (HQ). Some roles listed as hybrid. - **Notable Perks**: - Competitive salary ranges (e.g., Platform Engineer: $140K – $250K; other roles $70K – $120K). - Opportunity to shape the infrastructure that leading AI labs depend on. - Fast‑paced startup environment with high ownership. ## Sources 1. [Y Combinator – HUD](https://www.ycombinator.com/companies/hud) 2. [LinkedIn – HUD](https://www.linkedin.com/company/hud-evals) 3. [Built In San Francisco – HUD](https://www.builtinsf.com/company/hud) 4. [Latka – HUD](https://getlatka.com/companies/www.hud.so) 5. [Hud Careers Page](https://jobs.ashbyhq.com/hud) ## Other roles at HUD - [Security Engineer](https://feeny.ai/job/security-engineer-hud-san-francisco-ped7mf15dzhf) — San Francisco, CA - [Full-Stack Software Engineer, Reinforcement Learning](https://feeny.ai/job/full-stack-software-engineer-reinforcement-learning-hud-san-francisco-j072pqy2sdyd) — San Francisco, CA - [Lead Research Engineer, Data Quality](https://feeny.ai/job/lead-research-engineer-data-quality-hud-san-francisco-394mwe6veyfg) — San Francisco, CA - [Research Engineer, Synthetic Data](https://feeny.ai/job/research-engineer-synthetic-data-hud-san-francisco-nr8xjzh0398z) — San Francisco, CA - [Research Engineer, Benchmarks](https://feeny.ai/job/research-engineer-benchmarks-hud-san-francisco-wjf8abeym8d7) — San Francisco, CA - [Research Engineer, QC Automation](https://feeny.ai/job/research-engineer-qc-automation-hud-san-francisco-w32xstbv187y) — San Francisco, CA - [Forward Deployed Research Engineer](https://feeny.ai/job/forward-deployed-research-engineer-hud-san-francisco-t766zptzg625) — San Francisco, CA - [Recruiter](https://feeny.ai/job/recruiter-hud-san-francisco-xw2dz4wpr8ty) — San Francisco, CA - [GTM Engineer](https://feeny.ai/job/gtm-engineer-hud-san-francisco-d7nyzfj2e34w) — San Francisco, CA - [Growth Lead](https://feeny.ai/job/growth-lead-hud-san-francisco-3b9g4js2kfn7) — San Francisco, CA