Drimva

Veeva Systems

Senior Technical Product Manager (AI) - Vault Medical

$120K–$200K

Massachusetts - Boston · Remote · Manager · Full-time · Posted Sep 1, 2026

Experience
7+ years in enterprise software product management, engineering, or data science; 2+ years focused hands-on on AI/ML applications, specifically LLMs and Generative AI.
Education
Bachelor’s degree in engineering, computer science, or a related discipline.
Visa sponsorship
Candidates must be legally authorized to work in the USA or Canada.

About the job

Designs and delivers AI agent solutions for Vault Medical to automate medical affairs content workflows while ensuring compliance.

What you'll do

  • Design, prototype, configure, and validate solutions; write product specifications and actionable engineering requirements.
  • Lead production-ready AI agent design, including data orchestration, RAG architectures, and prompt engineering.
  • Identify high-impact AI use cases and track KPIs to demonstrate value and ROI.

What they ask for

  • 7+ years of enterprise software product management, engineering, or data science experience.
  • 2+ years of hands-on focus on AI/ML applications, specifically LLMs and Generative AI.
  • Strong coding skills, experience with AI frameworks and APIs, and knowledge of data flow design, prompt engineering, and model fine-tuning.
  • Bachelor’s degree in engineering, computer science, or a related discipline; must be based in a region in the Eastern Standard Time zone and legally authorized to work in the USA or Canada.

Nice to have

  • Direct experience with Veeva Vault Medical.
  • Familiarity with life sciences scientific literature workflows or experience in data science, machine learning, or data engineering.

Pay

USD 120,000 - 200,000 base salary

Tools

Python, LangChain, LlamaIndex, APIs, LLMs, Generative AI, RAG

AI focus

Build AI agents using LLMs and Generative AI to automate medical review, scientific literature publishing, and medical information response generation; work includes orchestration, RAG, prompt engineering, and model fine-tuning.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 6, 2026 (UTC)