Data and AI Product Manager

Grip is the AI-powered, end-to-end event platform built for engagement. The flexible system helps commercial event organisers like Ascential, Hyve, Emerald and Clarion Events boost revenue by establishing, maintaining and tracking relationships between participants over multiple events. This is possible because Grip goes beyond networking. It combines AI with billions of interactions happening across the platform with a powerful event management system, seamless registration and award-winning mobile event app so participants meet the right people at the right time.

We're looking for a Product Manager who thinks agentically, someone who approaches data not as an end in itself, but as the foundation that makes intelligent, AI-powered systems possible.

Grip is building toward a platform where AI agents act on behalf of organisers and participants. To get there, the data that underpins that layer needs to be right. That's where this role starts: getting hands-on with data ingestion, understanding how data moves through the platform, and building the clean, well-structured data layer that agentic systems depend on.

You'll work on system integrations, ETL pipelines and CDP tracking, not as traditional data plumbing work, but with a clear eye on what the AI layer above it will need. You'll be the person asking "is this data structured in a way an agent can use?" before asking "does this data exist?". As that foundation takes shape, your scope expands naturally into Grip's MCP design, agentic workflows and AI system architecture.

In your own workflow, agentic tooling is already the default. You use Claude Code, GitHub automations and agents to manage your output, not because you were asked to, but because it's simply how you operate.

This position is a remote role based in the UK.

Diagnose and resolve current data integration challenges within Engage, with a clear view of how clean data enables AI capabilities downstream.

Own the product roadmap for data integrations, mapping how data flows through Grip and shaping it for both current reporting needs and future agentic use.

Drive API integration work with organiser systems, third-party providers and enterprise platforms, always considering how data will be consumed by AI systems.

Work with data engineers on ETL pipeline design and dataset structure, thinking about what format and fidelity AI agents will require.

Maintain and evolve event tracking via our CDPs to ensure data is complete, accurate and machine-usable.

Define success metrics and build feedback loops that keep product decisions grounded in data.

Expanding into AI & agentic - as your scope grows

Contribute to MCP tool design, shaping how Grip's data is exposed and consumed within agentic systems.

Work with the Data and AI squad to identify where agentic capabilities create genuine product value.

Develop working knowledge of monitoring, evaluation and security for AI systems.

How you work

Run squad ceremonies, standups, sprint planning, backlog refinement and retrospectives.

Work closely with engineering leads to manage trade-offs, resolve blockers and maintain a healthy backlog.

Default to agentic tooling, Claude Code, GitHub automations and agents, to manage your own workflows, solve problems and contribute to minor fixes.

We are highly invested in your development, and your career path will be a standing, dedicated item in your regular check-ins with your line manager. As a Product Manager at Grip you will have plenty of opportunities to grow and try new things, leading others or owning technical initiatives across the organisation. We operate with a clear progression framework and use quarterly performance reviews to reflect and set goals so that you can achieve your full potential.

A PM who thinks agentically, your instinct when looking at a data problem is to ask what an AI system would need from it, not just what a dashboard would show.

3+ years of product management experience with a strong data background, ideally in technical or platform roles.

Solid understanding of data architecture and ETL pipelines. You can have a credible conversation with a data engineer about ingestion, transformation and how data is structured for downstream use.

Literate in APIs and integration patterns. You can interrogate a data contract and de-risk integration work alongside engineers.

Experience with CDPs, tracking plans, managing pipelines and ensuring data quality.

A working understanding of what makes data usable for AI, vector embeddings, structured outputs, context windows. You follow developments in MCP and agentic tooling and are actively building knowledge in this space.

Agentic tooling is already part of your workflow. Claude Code, automation agents and similar are defaults, not experiments.

Clear communicator across technical and commercial audiences.

Experienced in agile environments within a B2B SaaS or scale-up context. Bonus Points:

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.