Lead Product Manager - Data Platform

Innovate with purpose

At BILL, we believe in empowering the businesses that drive our economy. By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations. And we don’t stop there: we’re creating the future of financial automation so businesses can spend more time on what matters.

Working here means you become part of a vision-driven team that’s ready to tackle challenges and build cutting-edge solutions. We value purpose, drive, and curiosity—and we thrive in a fast-paced, ever-changing environment. Whether in one of our offices in San Jose, CA, Draper, UT, or working remotely, BILLders collaborate to deliver real impact for businesses that need more time in their busy weeks.

At BILL, we listen, learn, and lead—fostering collaboration and a drive for continuous growth. We’re committed to building a diverse and inclusive workplace that values each person’s unique skills and experiences. Even if you don’t meet every requirement, we’d love to hear from you—you might be just what we’re looking for, whether in this role or another.

✨ Let’s give businesses more time for what matters.

Lead Product Manager - Data Platform

We are seeking a strategic and experienced Lead Product Manager to drive the development of our AI & Data Platform. This critical role involves defining and executing the strategic vision for the platform, with a focus on enabling advanced data ingestion & storage, data processing, data serving, and applied AI capabilities. The ideal candidate will possess a deep understanding of data engineering, machine learning & AI workflows, and data science & analytics workflows, coupled with a passion for delivering scalable and high-performance data solutions

Responsibilities:

• Develop and communicate a comprehensive platform strategy, aligning with business goals, data governance standards, and the needs of diverse data users, including data engineers, ML/AI engineers, data scientists, analysts, and business stakeholders.
• Collaborate with engineering, data scientists, and analytics teams to build consensus for a customer-centric data vision and strategy. Drive this vision in a fast-paced environment by creating bold product roadmaps and participating in all levels of execution to deliver key results.
• Define and prioritize AI & data platform capabilities, including data ingestion and transformation for GenAI, real-time data pipelines for agentic systems, knowledge graph solutions for enhanced AI reasoning, enterprise feature stores for model development, and OLAP for analytical insights. Ensure alignment with evolving business requirements and emerging AI trends.
• Develop strong value-based metrics and goals that guide the iterative learning and delivery model to validate solutions to the most important data platform challenges as they evolve over time.
• Champion an AI-first approach to platform development, conducting user research, and utilizing feedback to continuously improve and innovate data platform features and functionalities for agentic and GenAI use cases.
• Lead the development and enhancement of data infrastructure optimized for AI workloads, ensuring scalability, reliability, and performance of both batch and real-time systems.
• Oversee the integration and optimization of data pipelines and workflows, ensuring efficient data ingestion, transformation, and delivery for AI model training, inference, and agentic decision-making.
• Drive the evolution of our feature store and knowledge graph to enable advanced analytics, machine learning, and the development of sophisticated agentic systems.
• Collaborate with data science and AI engineering teams to support model deployment, operationalization, and continuous improvement.
• Ensure the data platform adheres to data governance, observability, and compliance standards, implementing robust data security and access controls.

We’d love to chat if you have:

• Ideally 6+ years of product management experience serving data platforms and products used by technical audiences, including data engineers, data scientists, and ML/AI engineers.
• Proven experience in product management, with a strong focus on data platforms, data infrastructure, or related areas, with a demonstrated understanding of the unique data requirements of AI.
• Deep understanding of data engineering concepts, including ETL, data warehousing, data lakes, streaming data, and real-time data serving, with a focus on how these concepts apply to AI.
• Experience with modern data technologies and architectures, including cloud-based data platforms (e.g., AWS, GCP, Azure), data pipelines, feature stores, and knowledge graphs, with specific experie