About Doximity

Doximity is the leading clinical AI company with the largest network of U.S. clinicians. Doximity’s AI-powered workflow platform is trusted by over 85% of U.S. physicians and 300+ health systems. Doximity’s mission is to help clinicians be more productive so they can provide better care for their patients.

At Doximity, we value curiosity, ownership, inclusion, and a commitment to making a meaningful impact. If you’re excited about solving complex problems that improve healthcare, we’d love to hear from you.

About the Role

We are hiring a Senior Product Counsel, R&D / AI to serve as the primary legal partner to Doximity’s AI team. You will sit with the engineers, data scientists, and product managers building our clinical AI products — ambient documentation, clinical search and answers, and AI-powered clinician workflows — and help them ship quickly and responsibly. This is a hands-on, high-judgment role for a lawyer who wants to be in the room where AI products are designed, not downstream of them.

As a Senior Product Counsel, R&D / AI, you will:

Act as embedded counsel to our AI and R&D teams, advising on product design, model development, and launch decisions from concept through release — and owning the most significant legal questions our AI organization faces.
Advise on health data throughout the AI lifecycle: HIPAA and HITECH, business associate arrangements, de-identification, permitted uses for model training and evaluation, and state health privacy and consent laws.
Counsel on AI-specific risk, including training data provenance and licensing, third-party model and API terms, output accuracy and reliability, clinical decision support and FDA software boundaries, intellectual property in AI outputs, and transparency and disclosure obligations.
Draft and negotiate the agreements R&D depends on — data licenses, model and infrastructure provider terms, research and clinical collaborations, BAAs and DPAs, and evaluation and pilot agreements.
Build the legal infrastructure that lets AI development scale: intake and review processes, product launch checklists, playbooks, self-service guidance, and training for engineering and product teams.
Partner closely with Privacy, Security, Regulatory, Clinical, Trust & Safety, and Marketing to align on governance for new AI capabilities.
Track the fast-moving AI and health data regulatory landscape and translate it into concrete, actionable product guidance.

Location: This role is In-Person in San Francisco, CA.

What We’re Looking For

We’re excited to meet candidates who have many of the following qualifications:

J.D. and active membership in the California bar (or eligibility to register as in-house counsel in California).
California Bar membership preferred; alternatively, an attorney licensed in any U.S. jurisdiction and eligible to obtain RHIC may be considered.
Approximately 10+ years of legal experience, including meaningful in-house time supporting a technology, digital health, or healthcare organization.
Demonstrated experience as product counsel — embedded with engineering and product teams, advising on features in flight rather than reviewing finished work.
Healthcare data fluency: HIPAA, business associate relationships, de-identification standards, and the practical realities of working with PHI. Digital health, health IT, or provider-facing experience strongly preferred.
Working knowledge of the legal issues specific to AI and machine learning — training data rights, model licensing, output liability, evaluation and monitoring, and emerging AI regulation.
Genuine hands-on facility with AI tools, and the technical curiosity to engage substantively with the people building models.
Comfort with ambiguity and a bias toward practical, risk-calibrated advice delivered at product speed.
Clear, concise written communication and the ability to make legal complexity actionable for a technical audience.

Compensation

The anticipated total compensation for this role is $257,000 - $350,000, depending on factors such as experience, skills, location, and internal equity.