Senior Product Manager, Data & AI

Afresh•San Francisco, CA

About The Position

Afresh is the leading AI company in fresh food—partnering with grocers like Albertsons, Wakefern, Meijer, and Stater Bros to order billions of dollars of fresh food in over 12,000 grocery departments nationwide. Following record-breaking 70% growth in 2025, we’ve expanded our platform to cover all fresh departments, launched our full store suite, and debuted DC Fresh Buying. We’re on a mission to eliminate food waste and make fresh food accessible to all. In 2025 alone our software helped save 200M lbs of food waste. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines the future of fresh, there is no better time to join us. About the role We're looking for a Senior Product Manager to lead our Data & AI product initiatives—the engine that powers Afresh's competitive advantage. Data is one of our key differentiators, directly impacting the success of our applied science and customer experience You'll lead 2-3 active customer integrations end-to-end, working hands-on with our data teams to identify bottlenecks, brainstorm solutions, and explore how AI tools can dramatically reduce integration time and improve our integration capabilities. These real-world integration experiences will directly inform your product strategy and enable you to build solutions that matter. You'll have the opportunity to explore and build new products that further differentiate our data platform and integration ability. Specifically, you'll lead the 0 to 1 build out of two new data products that productize our data capabilities and unlock new value for customers. You'll leverage AI throughout—from AI-powered debugging tools that help customers self-resolve issues, to AI-assisted integration development that accelerates our delivery, to intelligent data quality monitoring that proactively identifies and diagnoses problems. This role requires you to truly understand our data systems and the customer-facing needs of the integration experience. You'll conduct user research and work with design to build out user-facing data ingestion monitors, alerts, and debugging experiences. You'll be working with an incredibly hardworking team of engineers, designers, and product managers to define and own the product vision for how AI can help us move faster, work better, and solve one of the toughest product problems we have—one that is absolutely critical to unlocking accelerated growth at Afresh.

Requirements

4+ years experience as a product manager in a fast paced environment
Strong experience product managing or developing data-centric products—you deeply understand data systems, pipelines, and quality challenges
Technical fluency that enables you to creatively explore possibilities and challenge constraints with engineering, with demonstrated ability to earn the respect of talented engineers
Strong analytical skills, with the ability to gather data, both qualitative and quantitative, emerge with insights, and make and communicate well-reasoned decisions
Excellent communication skills, logical reasoning, and storytelling, with proven ability to collaboratively work across a variety of stakeholders
Experience creating product roadmap(s) from conception to launch, driving product vision, defining go-to-market strategy and leading design discussions
Ability to thrive in ambiguity and build products from 0 to 1
Experience working closely with customer-facing teams and understanding customer pain points
Prefer experience with SaaS companies or B2B enterprise products

Nice To Haves

Experience with AI/ML products or platforms is a strong plus
Prefer experience with SaaS companies or B2B enterprise products

Responsibilities

Lead Customer Integrations
Own 2-3 active integrations end-to-end as primary integration lead
Bring structure and process optimizations to how the team runs integrations
Use learnings as input to integration velocity initiatives—this is critical to learning how our system works end-to-end
Drive Integration Velocity & Automation
Develop a roadmap for integration velocity, ambitiously aiming to cut our integration time by 60%
Explore and test vendors that can enable AI integration development or velocity
Identify and solution around bottlenecks in our system from both technical and operational perspectives
Own AI-powered initiatives to compress integration timelines, including Integration Assistant tooling and AI Integration Discovery projects
Build Automated Data Quality Products
Build a vision and product for automated and customer-facing data quality reporting and analytics
Productize data quality monitoring as a customer-facing feature with AI-powered debugging capabilities
Enable customers to have transparent visibility into their data health while leveraging AI to automatically diagnose issues and provide actionable insights
Own Data Products Holistically
Ensure our data models are best in class for how they model fresh data and solve fresh data problems
Understand how our data products are used by downstream teams (POP, SS, DC) and optimize for their needs
Partner with Store Solutions & DC PMs to define data requirements and translate them into automated data contracts and quality checks
Own the product strategy and execution of our data ingestion platform including our data model, data pipelines, relevant user interfaces, and data monitoring capabilities
Strategic Product Initiatives
Lead the scoping, definition, and eventual execution of how we monetize our data assets in Logic as a Service
Own product strategy and roadmap for Recipe Management
Communicate both the business and technical rationale behind your decisions and evangelize your vision
Cross-functional Collaboration
Work cross-functionally with our Deployment and Customer Success Teams, Engineering and Design to realize our product vision by taking products from conception to launch
Through user research and data analysis, develop user stories and product requirements, engage in usability and prototype testing, and define and monitor success metrics for maximal impact