Senior Product Manager
Job description
About the role
This role defines and delivers AI Agent capabilities for life sciences CRM products. The position owns end-to-end product design and translates complex workflows into agentic solutions.
Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.
Key facts
What you'll do
Product teams define agent goals, workflows, context, tool usage, and human-in-the-loop design to establish clear success criteria for solution development. Engineering, QA, and customer teams collaborate to deliver high-quality AI Agent capabilities and validate outcomes against requirements. Customer feedback and real-world product performance guide continuous iteration and improvement of AI Agent capabilities over time.
Requirements
Candidates work for 2+ years on a dedicated AI product team, shipping AI features as a core member of delivery. Professionals gain hands-on experience designing, delivering, or improving AI Agent products, including prompt and context engineering, human-in-the-loop workflows, and AI quality evaluation. Individuals bring 5+ years of experience in digital products, with demonstrated ownership of complex products or initiatives across discovery, design, delivery, launch, adoption, and ongoing improvement. Professionals lead customer discovery independently and communicate effectively with senior business stakeholders to shape product direction. Teams translate complex customer workflows and underlying business problems into clear product direction and solutions.
Practical notes
The role is based in China
Shanghai and follows a full-time schedule. Veeva is an equal opportunity employer who considers applicants without regard to protected characteristics. Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Good to know
AI product roles define agentic workflows and measurable outcomes. Success balances user needs with reliability, quality metrics, and iterative improvement. Enterprise SaaS, configurable platforms, and multi-tenant environments involve strict governance and integration requirements. Life sciences and regulated industries add constraints around compliance, security, and data privacy. Strong stakeholder communication bridges product, engineering, and customer expectations.
Questions to ask
Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, we surpassed $3B in revenue in our last fiscal year with extensive growth potential ahead.