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 hands-on focus 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 that automate Vault Medical content workflows while supporting compliant scientific communications.

What you'll do

  • Design, prototype, configure, and validate AI solutions; lead agent architecture, orchestration, RAG, and prompt engineering.
  • Define product specifications and actionable requirements, collaborating with Engineering, QA, UX, and Product Management.
  • Identify AI use cases and define KPIs to measure performance and stakeholder value.

What they ask for

  • 7+ years of enterprise software product management, engineering, or data science.
  • 2+ years of hands-on AI/ML application work, specifically with LLMs and Generative AI.
  • Strong coding skills, such as Python; experience with AI frameworks and APIs; 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 an Eastern Standard Time zone region 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 - USD 200,000 base salary

Tools

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

AI focus

Build production-ready AI agents for Medical Affairs workflows, including content review, scientific literature publishing, and medical information responses; work includes orchestration, RAG, prompt engineering, and defining AI success metrics.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)