Associate General Counsel – Regulatory and Technology

Pathos; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Pathos is seeking a primary legal advisor to support the engineering, product, and clinical teams in the development of AI platforms for cancer treatment. This role requires FDA drug development law expertise and the ability to understand complex data systems.

The successful candidate will thrive in ambiguity, possess a J.D. from a top law school, and have at least 7 years of experience in relevant legal environments. This position offers the opportunity to create a regulatory infrastructure from scratch and engage with innovators in the biotech field.

Qualifications

• 7+ years of legal experience, preferably with in-house experience in tech/biotech.
• Experience with IND/NDA/BLA lifecycle, GCP, and AI/ML regulatory frameworks.
• Familiarity with clinical data standards and real-world evidence.

Responsibilities

• Advise on FDA regulatory strategies related to AI platforms.
• Develop and maintain compliance programs for privacy and data governance.
• Engage with internal teams on technical specifications and data flow designs.

Skills

FDA drug development law

Regulatory compliance

Data governance

Technical aptitude

Cloud infrastructure understanding

Education

J.D. from a top law school

Job description

About the role

This role is one of the most direct applications of legal expertise to the treatment of cancer. 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. 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.