Senior Technical Product Manager (AI) - Vault Medical
New
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Veeva SystemsLife sciences software
United States, Eastern Standard Time (EST)Full-TimeSenior
SalaryBase pay: $120,000 - $200,000
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Job Details
- Experience
- 7+ years of enterprise software product management, engineering, or data science; 2+ years of hands-on focus on AI/ML applications, specifically LLMs and Generative AI
- Required Skills
- PythonRESTful APIsData modelingPrompt EngineeringGenerative AILangChain
Requirements
- Have 7+ years of enterprise software product management, engineering, or data science experience.
- Have 2+ years of hands-on focus on AI/ML applications, specifically LLMs and Generative AI.
- Have strong coding skills, including experience with Python.
- Have experience with AI frameworks such as LangChain or LlamaIndex and with APIs.
- Understand data flow design, prompt engineering, and model fine-tuning for highly regulated content.
- Be able to translate complex AI concepts into business value for non-technical stakeholders in Legal, Medical, and Regulatory departments.
- Have a proven track record of working with UX and Engineering to build intuitive tools for complex workflows.
- Have experience with data modeling, including ERDs.
- Be able to work independently in a fast-paced environment and be comfortable with ambiguity.
- Have a bachelor's degree in engineering, computer science, or a related discipline.
- Be based in a region in the Eastern Standard Time zone.
- Nice to have direct experience with Veeva Vault Medical, familiarity with scientific literature planning, authoring, review, submissions, or publishing, or experience in data science, machine learning, or data engineering.
Responsibilities
- Design, prototype, define, configure, and validate solutions to address customer problems.
- Design and iterate on product solutions.
- Author high-quality specifications and communicate actionable requirements to engineering teammates.
- Work with Engineering, QA, and Product Management to build solutions across Veeva applications.
- Lead the design of production-ready AI agent applications, with a focus on data flow orchestration, RAG architectures, and prompt engineering.
- Identify high-impact use cases for LLMs in Medical Affairs workflows.
- Define and track KPIs for AI success and demonstrate ROI to stakeholders.
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