Data and AI Product Manager

Grip

1d•Remote

About The Position

Grip is seeking a Product Manager who thinks agentically and views data as the foundation for intelligent, AI-powered systems. This role focuses on building a clean, well-structured data layer essential for AI agents, involving hands-on work with data ingestion, system integrations, ETL pipelines, and CDP tracking. The scope will expand to include Grip's MCP design, agentic workflows, and AI system architecture. The ideal candidate already utilizes agentic tooling in their own workflow, such as Claude Code and GitHub automations. This is a remote role based in the UK.

Requirements

A Product Manager with an agentic mindset, prioritizing AI system needs for data problems.
3+ years of product management experience with a strong data background, preferably in technical or platform roles.
Solid understanding of data architecture and ETL pipelines.
Ability to engage in credible conversations with data engineers about ingestion, transformation, and data structuring.
Proficiency in APIs and integration patterns, capable of interrogating data contracts and de-risking integration work.
Experience with CDPs, tracking plans, managing pipelines, and ensuring data quality.
Working understanding of data usability for AI, including vector embeddings, structured outputs, and context windows.
Familiarity with developments in MCP and agentic tooling, actively building knowledge in this area.
Agentic tooling (Claude Code, automation agents) is already part of your workflow.
Clear communicator across technical and commercial audiences.
Experienced in agile environments within a B2B SaaS or scale-up context.

Nice To Haves

Direct exposure to building AI-first features or agentic workflows.
Familiarity with MCP tool design, vector databases, or AI system monitoring and security.
Experience in event tech, MarTech, or platforms with complex multi-system data flows.

Responsibilities

Building the data layer for agentic systems, diagnosing and resolving data integration challenges to enable AI capabilities.
Owning the product roadmap for data integrations, mapping data flows and shaping them for reporting and future agentic use.
Driving API integration work with organizer systems, third-party providers, and enterprise platforms with a focus on AI consumption.
Collaborating with data engineers on ETL pipeline design and dataset structure for AI agent requirements.
Maintaining and evolving event tracking via CDPs to ensure data completeness, accuracy, and machine usability.
Defining success metrics and building feedback loops for data-grounded product decisions.
Contributing to MCP tool design, shaping data exposure and consumption within agentic systems.
Working with the Data and AI squad to identify valuable agentic capabilities.
Developing working knowledge of monitoring, evaluation, and security for AI systems.
Running squad ceremonies, including standups, sprint planning, backlog refinement, and retrospectives.
Collaborating with engineering leads to manage trade-offs, resolve blockers, and maintain a healthy backlog.
Utilizing agentic tooling (Claude Code, GitHub automations, agents) for personal workflows, problem-solving, and minor fixes.