Commercial and IP Counsel

- Partner closely with the sales team to draft, negotiate, and close API and enterprise agreements.

- Build scalable contracting infrastructure - templates, negotiation playbooks, risk-tiering, and a contract lifecycle process - so the business can move at startup speed as deal volume grows.

- Negotiate compute and infrastructure agreements with cloud and GPU providers and agreements with foundation-model or technology partners, including model-hosting, API-reseller, and co-development deals.

- Structure and negotiate data licensing and content-partnership agreements for training and fine-tuning datasets- covering scope of use, exclusivity, attribution, and downstream rights.

- Advise research and engineering on IP ownership for training methods, model weights, checkpoints, and derivative/fine-tuned models, including questions raised by open-weight releases and third-party model integration.

- Advise on open-source and third-party license compliance for code, model weights, and datasets used in research and production (e.g., copyleft obligations, model license restrictions, attribution requirements).

- Advise on copyright and data-rights issues in sourcing, licensing, and using training and fine-tuning data, including scraped, licensed, user-generated, and synthetic data.

- Work with internal stakeholders on output-side IP risk: substantial-similarity and infringement exposure in generated video/image/3D content, style-mimicry claims, and takedown/DMCA processes.

- Advise on content provenance and authenticity questions as they intersect with commercial terms and emerging regulations.

- Review and advise on Customer DPAs and privacy questionnaires.

- J.D. and active membership in at least one U.S. state bar.

- 5+ years of experience spanning law firm and in-house work, with substantial time on technology commercial transactions and IP.

- Proven track record negotiating SaaS/API agreements, data licensing deals, and cloud/compute or infrastructure contracts with minimal supervision.

- Working technical fluency with how generative AI models are built and deployed - training data pipelines, fine-tuning/distillation, model weights and checkpoints, inference serving - sufficient to negotiate terms and issue-spot without translation from engineers.

- Substantive experience with the IP issues specific to AI: copyright and training-data rights, output ownership and infringement risk, open-source/open-weight model licensing, and patentability of ML techniques.

- Familiarity with the emerging AI regulatory landscape (e.g., EU AI Act, U.S. state AI laws, content-provenance/disclosure rules) and how it intersects with commercial and IP terms.

- Excellent judgment on balancing legal risk against the pace of a frontier research company - comfortable operating without settled precedent.

- A builder's mindset: energized by creating process and infrastructure where none exists yet, not just executing an existing playbook.

- Clear, direct communicator who can explain complex legal and technical tradeoffs to researchers, engineers, and executives alike.

- Bonus: prior in-house experience at a foundation model lab, AI infrastructure company, or developer platform; technical background (CS/EE) or fluency reading ML papers.