AstraZeneca
Product Line Lead, Clinical & Agentic AI
$182K–$272K
US - Boston - MA · Full-time · Posted Oct 30, 2026
- Experience
- 10 or more years; no stated alternatives.
- Education
- At least a Master's degree or PhD in life sciences, data science, computer science, engineering, or a related field. An advanced degree is desirable.
About the job
Leads the clinical and agentic AI product line, taking clinical agents from proof of concept to validated use and setting direction for the supporting platform.
What you'll do
- Own product-line strategy, roadmap, priorities, lifecycle gates, success measures, and portfolio reporting.
- Lead product owners and delivery, including the CRA agent’s path to GxP-validated release and coordination with engineering and delivery partners.
- Set platform direction and ensure products address human oversight, validation, privacy, governance, risk, and audit readiness.
What they ask for
- 10 or more years of product management or product leadership experience, including leading other product owners or managers.
- Experience in pharmaceutical, biotechnology, or other regulated healthcare technology settings, with a track record of taking products from proof of concept to validated production use in a regulated environment.
- Working knowledge of clinical development or clinical operations processes, familiarity with agentic and LLM-based products, and understanding of GxP validation and data privacy requirements.
- At least a Master's degree or PhD in life sciences, data science, computer science, engineering, or a related field.
Nice to have
- Experience with clinical systems such as EDC and CTMS.
- Experience with platform product management and build, buy, or adopt decisions; working knowledge of Atlassian tools (JIRA, Confluence).
Pay
$181,570.4 to $272,355.6 USD — base pay
Tools
LLM, EDC, CTMS, JIRA, Confluence
AI focus
Leads agentic AI products for clinical development and operations, including the CRA agent, and sets direction for the R&D agentic platform. Ensures appropriate evaluation, human oversight, validation, and governance, including decisions about patient-data use on governed platforms versus enterprise assistants.
Model-written summary · the original posting is authoritative