Contract Medical Safety Expert (Pharma MD) – AI-Driven Adverse Event Detection

About Us

Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs as part of our Polaris constellation, resulting in a system with over 99.9% accuracy.

Why Join Our Team

Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation.

Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA.

Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others.

Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative.

About the Role

We are seeking an experienced Pharmaceutical Safety Medical Doctor with a proven background in health technology to join our cross-functional team as a Contract Medical Safety Expert. This role is central to developing and validating an AI-powered adverse event (AE) detection engine that can accurately identify and categorize FDA-reportable events from unstructured and structured medical data.

This contractor will play a key role in helping Hippocratic AI create a robust system that meets regulatory standards and clinical expectations while working at the intersection of pharmacovigilance, clinical safety, and cutting-edge artificial intelligence.

What You'll Do

• Subject Matter Expertise: Provide expert clinical and regulatory guidance on pharmacovigilance, especially around US FDA requirements for AE reporting and MedWatch compliance.

• AI Model Development Collaboration:

  • Partner with the AI/ML and Clinical Informatics teams to design annotation schemas and decision logic related to AE identification.

  • Define clinically validated criteria to distinguish reportable vs. non-reportable events.

  • Contribute to the design and refinement of classification taxonomies for adverse events, seriousness, and expectedness.

• Quality & Safety Oversight:

  • Review model outputs and participate in error analysis of AI-generated AE classifications.

  • Help define “safe fail” protocols for uncertain or ambiguous cases.

• Data Strategy Support:

  • Inform data collection strategies and guide labeling/annotation efforts for adverse event corpora.

  • Collaborate on test sets that simulate real-world AE reporting cases across various therapeutic areas.

• Regulatory Alignment:

  • Ensure compliance with FDA pharmacovigilance standards (21 CFR Part 314, ICH E2A/E2D, etc.).

  • Liaise with internal quality and regulatory stakeholders to audit model readiness for future deployment.

• Stakeholder Communication:

  • Summarize clinical safety perspectives for cross-functional leadership and potential external partners.

  • Contribute to documentation supporting FDA or regulatory body interactions, if required.

What You'll Bring

Must-Have:

• MD (Doctor of Medicine) with board certification strongly preferred.

• 5+ years of experience in pharmacovigilance or drug safety within a pharma, biotech, or CRO environment.

• At least 2 years of experience collaborating with or working at a health tech or AI/ML-focused company, ideally involving clinical data or regulatory technology products.

• Strong familiarity with FDA AE reporting requirements, MedDRA, and ICH E2B guidelines.

• Clinical expertise in therapeutic areas such as primary care, internal medicine, or neurology is a plus.

• Experience working with or reviewing outputs from NLP/LLM or AI-based systems is highly desirable.

• Exceptional attention to detail, with a strong sense of clinical judgment and ethical responsibility.

<