Senior Product Manager

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.

At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.

Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.

We are seeking an experienced Senior Product Manager to join our product team, focusing on our suite of products for the life sciences industry. You will be responsible for the product direction and execution for key components. This role will focus on enhancing our SaaS solutions to help life sciences companies improve the effectiveness of their key commercial operations.

Work closely with customers to understand their business challenges, workflows, and requirements.

Translate customer needs into clear product requirements and scalable product solutions.

Manage the full product lifecycle, including market research, product planning, development, launch, adoption, and continuous improvement.

Identify product improvement opportunities and define and maintain the product’s mid- to long-term roadmap.

Define AI Agent use cases, including agent goals, workflows, context, tool usage, human-in-the-loop design, exception handling, and success criteria.

Work with Engineering, Design, Data, QA, and Solution Consulting teams to deliver high-quality AI Agent capabilities.

Define and monitor AI product quality metrics such as accuracy, task completion, reliability, user trust, adoption, and business value.

Use customer feedback and real-world product performance to continuously improve AI Agent capabilities.

Provide cross-functional leadership to align priorities, drive decisions, and ensure successful product delivery and go-to-market.

7+ years of experience in digital products, AI solutions, or a related field, with demonstrated ownership of complex products or initiatives across the full lifecycle, from discovery and design through delivery, launch, adoption, and ongoing improvement.

Extensive customer-facing experience, with the ability to independently lead customer discovery and communicate effectively with senior business stakeholders.

Strong ability to understand complex customer workflows, identify the underlying business problems behind stated needs, and translate ambiguous requirements into clear product direction and solutions.

Hands-on experience designing, delivering, or continuously improving Generative AI, conversational AI, or AI Agent products.

Experience designing AI Agent use cases, including defining agent goals, workflows, context requirements, tool usage, human-in-the-loop mechanisms, exception handling, and success criteria.

Ability to define and evaluate AI product quality across dimensions such as accuracy, task completion, reliability, user trust, product adoption, and business value.

Strong product judgment, with the ability to challenge assumptions, make thoughtful trade-offs, and clearly explain product decisions to customers and internal stakeholders.

Proven cross-functional leadership, with the ability to build alignment with Product and Engineering teams, drive collaboration, and influence outcomes.

Ability to operate independently in a fast-moving, ambiguous, and highly customer-facing environment.

A high degree of professional ethics, integrity, accountability, and commitment to customer success.

Experience with enterprise SaaS products, configurable platforms, or multi-tenant product environments.

A technical background in software engineering, computer science, data science, machine learning, solution architecture, or a related field.

Familiarity with concepts such as large language models, RAG, prompt and context design, tool calling, agent orchestration, APIs, and enterprise data integration.

Experience in life sciences, pharmaceutical commercial operations, medical affairs, CRM, or another regulated industry.

Experience designing products that use enterprise data, knowledge bases, unstructured content, or external information sources.

Familiarity with AI governance, data privacy, information security, compliance, auditability, and responsible AI practices.