Drug development shouldn’t be guesswork, not when patients are waiting.
Pathos is building a next-generation biotech with AI at the core. Not as a feature, but as the operating system for how medicines get developed. We believe most drugs don't fail because the science was wrong. They fail because they were tested in the wrong patients, with the wrong assumptions, in trials that couldn't answer the real question: who benefits, and why?
Pathos exists to change that. We're building the largest foundation model in oncology and pairing it with proprietary AI systems, deep oncology expertise, and 200+ petabytes of multimodal data linked to patient outcomes, so we can make development decisions with more precision, much earlier.
This is not theoretical. We’re well-capitalized and have the leadership to build a generational company. We invest in and advance our own clinical-stage programs, using our AI platform to sharpen trial design, patient selection and biomarker strategy. So therapies reach the patients most likely to benefit, sooner.
How We Build
Pathos does not operate like a traditional biotech. There is no middle management. There are no layers of approval. The company is designed, from the ground up, around small teams of 2–4 subject matter experts who each command hundreds of AI agents to do the work that used to require dozens of people.
Everyone builds. Everyone ships. Every function at Pathos — from clinical execution to asset selection to the foundation model itself — runs on this model. Our product velocity delivers meaningful outcomes in hours instead of weeks. This is not a future aspiration. It is how we operate today.
The people who thrive here are operators: deep experts who can specify what needs to happen, orchestrate AI agents to execute at scale, and make high-judgment calls that compound over time. If you have spent your career building and shipping AI systems at scale, this is the environment where that experience becomes a superpower.
About the role
This role is one of the most direct applications of legal expertise to cancer research. You will be the primary legal advisor to the engineering, product, and clinical and operations teams building four of the company’s core platforms: the Oncology Foundation Model, AI Platform Foundry, Scout (asset identification), and Sprint (clinical trial execution).
You will arrive with deep expertise in FDA drug development law and a genuinely meaningful ability to engage with how software systems are built and how data moves through them. You will learn the company’s technical stack well enough to represent it accurately in conversations with regulators, partners, and investors — not to operate it, but to articulate it with precision. You have technical aptitude, and a track record of learning new technology in a real way.
Your default answer is not “no,” it’s “here’s what it will take to do this right.” You understand the team’s objectives, consolidate the requirements, and advise on how to structure the work in a risk-reduced yet still innovative way - with advocacy in your toolset if needed. This is a build role - there is no infrastructure to inherit, meaning you will create it from scratch and run it with AI agents as your force multiplier.
Key Responsibilities
Advise on all things regulatory. Drug development, privacy, corporate compliance, AI guidelines, etc.
Own all things regulatory + compliance that don’t already have a home outside Legal. For instance, Finance will own tax compliance, but you’ll be owning the privacy program
Uplevel and own the company’s compliance program
Maintain organized digital spreadsheets of everything
Learn and use AI to force multiply yourself across legal workstreams
Regulatory Counseling
Advise on FDA regulatory strategy and classification for all components of the AI platform, including implications for development, commercialization, and IND/NDA/BLA submissions (FDA submissions will be owned by Regulatory Affairs)
Advise on protocol development, site monitoring, data integrity, biomarker qualification, companion diagnostic considerations, the use of real-world data, etc.
Monitor and interpret evolving FDA guidance on AI/ML in drug development and translate into actionable guidance for internal teams
Support direct engagement with the FDA and other agencies on novel questions when warranted, including in global clinical programs
Review external content such as conference publications for regulatory issues
Product and Technology Counseling
Inform and review tech product specs, system architectures, and data flow designs for regulatory risk before build and deployment
Develop working knowledge of the company’s technical stack — cloud infrastructure, data pipelines, storage systems, and model architecture — sufficient to accurately represent those systems to regulators, partners, and investors
Advise on data governance, data integrity, chain-of-custody, and 21 CFR Part 11 requirements for clinical data across company systems and third-party infrastructure
Structure HIPAA and applicable data privacy frameworks; develop and maintain internal regulatory policies and compliance frameworks for AI tool development and deployment
Track and assess evolving AI regulation (EU AI Act, FDA AI governance frameworks, state laws) for applicability to company activities
Alongside AGC - Transactions, support the General Counsel on additional legal matters as part of a centralized, high-performing G&A team also comprising People Operations, IT, and Recruiting
Who you are
Required Qualifications
J.D. from a top law school and active bar admission
7+ years of legal experience with substantial in-house time, preferably at a high-growth technology / biotech company
Existing expertise in drug development law: IND/NDA/BLA lifecycle, GCP, 21 CFR Part 11, and regulatory frameworks governing AI/ML tools and software in drug development
Demonstrated experience advising engineering or product teams, with the ability to understand and accurately articulate complex technical systems — cloud infrastructure, data pipelines, ML model architecture — without being a practitioner
While this role requires no scientific background, you'll work alongside world class researchers and technologists in a state of the art facility, and will need to be able to match the pace of the rest of the team
Track record of building regulatory strategy from first principles and owning a regulatory and technical narrative with pharma partners, investors, and regulators
You notice when something is out of place and fix it - without being asked or waiting to see if someone else notices and does it first
Thrives in ambiguity. You're comfortable working without a playbook, you figure it out, get it done, and write the process down so it's faster next time.
Familiarity with clinical data standards, real-world evidence, biomarker qualification, or adaptive trial design.
Preferred Qualifications
Background at an AI-in-drug-development, precision medicine, or genomics company.
Exposure to basic IP principles: portfolio management, prior art review.
Originally posted on Himalayas