Associate Director/Director, Frontier and AI Product Counsel

Your Impact at LILA

As Associate Director/Director, Frontier and AI Product Counsel at Lila Sciences, you will be the dedicated legal partner to the teams building Scientific Superintelligence™ — our AI research organization, our AI Science Factory™ platform, and the data, safety, and security functions that support them. You will own the legal questions that come with training frontier models on scientific data and running experiments autonomously: where data comes from and what we can do with it, how rights are allocated when we discover something alongside a partner, what we can publish or open-source, and how we build, evaluate, and release capable systems responsibly.

This is deliberately a build role, not a maintenance role. Much of this work has no settled precedent and no off-the-shelf playbook — you will frequently be designing the framework rather than applying one. You'll partner daily with scientists, ML researchers, platform engineers, and our safety and security teams, and closely with our privacy, commercial, and go-to-market colleagues as the platform is deployed, and you'll be the person who translates between technical reality and legal risk in both directions.

This role reports to the Vice President, Associate General Counsel, Product and is scoped for an experienced attorney with 7–12 years of experience who wants to work at the intersection of law, AI, and science, and who is energized rather than unsettled by novel questions. You should be comfortable with ambiguity, opinionated about risk, and willing to sit with a research team long enough to actually understand what they're building.

What You'll Be Building

Data and model development

• Advise research and data teams on permissible data usage across the training pipeline, and build the provenance and acquisition frameworks that govern what goes into Lila's models
• Serve as a subject matter expert on copyright, licensing, privacy, and contractual restrictions as applied to training data — public, licensed, synthetic, open-source, and partner-contributed alike
• Support structuring and negotiation of data licensing, material transfer, consortium, and research collaboration agreements with academic, clinical, and industry partners, including how rights in data, models, and derived outputs are allocated

Release and disclosure

• Advise on release decisions for models, agents, tools, and datasets, including open-weight strategy and the application of open-source licenses to incoming and outgoing code, data, and model artifacts
• Coordinate legal readiness for model and platform launches — model documentation and system cards, capability evaluations, and review of pre-release and internal-only models
• Support publication and disclosure review, balancing scientific openness against partner obligations and safety considerations
• Counsel research teams on research design, data collection and sharing, external collaborations, and program launches, including alignment, interpretability, and societal-impact work as those functions develop
• Counsel platform teams on legal considerations for autonomous experimentation and agentic systems

Safety, security, and dual-use

• Partner with our AI Safety and AI Security teams on the legal dimensions of technical mitigations, evaluations, red-teaming, and misuse prevention, including vendor engagements and external collaborations
• Advise on dual-use and biosecurity considerations arising from autonomous chemistry and biology, including screening, access controls, and disclosure
• Help operationalize Lila's safety framework as capabilities scale: how capability thresholds translate into evaluations, access controls, documented mitigations, and release decisions
• Serve as a first-line contact for safety and security escalations, and build the playbooks that let that response scale

Regulation and infrastructure

• Track and translate the regulatory landscape that bears on our work: emerging AI regimes (EU AI Act, US state AI laws), health and research data rules, human-subject and biospecimen requirements, and export controls
• Support compute and infrastructure arrangements, including cloud and datacenter agreements, cross-border data transfers, and data localization
• Represent Lila in regulatory inquiries, and contribute to industry and academic work on data governance and safety norms for AI-driven science

Building the function

• Design the frameworks, templates, and self-serve guidance that put legal judgment in the hands of the teams who need it, and use AI tools aggressively to extend the reach of a small team

What You'll Need to Succeed

• J.D. and membership in at least one U.S. state bar in good standing
• 7–12 years of legal experience, with substantial time in-house at a technology, AI, or life sciences company, ideally spanning both research-facing and product- or customer-facing counseling
• Depth in at least two of: copyright and IP, data licensing and provenance, privacy and data protection, AI regulation, model launch and deployment counseling, or research and collaboration transactions — and the appetite to get up to speed fast on the rest
• Genuine technical fluency: you can hold your own in a conversation about how models are trained, evaluated, and deployed, you can read a research protocol without needing it translated, and you can spot the legal issue inside a technical design
• Sound judgment under uncertainty, and the ability to give clear, practical advice on questions where the law has not caught up, including when to be flexible and when to hold a line
• A strong sense of ownership and the instinct to build cross-functional relationships, so teams bring you in while decisions are still open rather than after them
• Excellent written communication — you can draft a policy, a framework, or a whitepaper that non-lawyers will actually use
• Comfort operating outside your areas of expertise, wearing many hats, and moving at startup speed without losing rigor

Bonus Points For

• A STEM background or advanced degree, particularly in biology, chemistry, materials, or computer science
• Experience advising AI research teams on training data, model development, or model release decisions
• Experience advising on enterprise or API product deployment — data governance, tenancy and access controls, connectors, or agentic features
• Experience coordinating model launches, or drafting model documentation, system cards, or capability evaluation write-ups
• Experience with AI-generated invention and inventorship questions, or patent strategy in an AI-driven discovery setting
• Familiarity with dual-use, biosecurity, export control, or CFIUS considerations
• Experience supporting academic collaborations, consortium agreements, or federally funded research
• An academic or publishing background, or depth in open-source and data licensing
• Experience engaging directly with regulators or standards bodies
• Experience building legal infrastructure and scalable processes from scratch
• Enthusiasm for transforming legal practice through AI and data-driven tools