数据与人工智能产品经理
Data and AI Product Manager
🚀 我们是谁?
Grip 是一个由人工智能驱动的端到端活动平台,专为提升参与度而设计。灵活的系统帮助 Ascential、Hyve、Emerald 和 Clarion Events 等商业活动组织者通过在多个活动中建立、维护和跟踪参与者之间的关系来提高收入。这是因为 Grip 超越了单纯的社交。它将人工智能与平台上数十亿次互动相结合,搭配强大的活动管理系统、无缝注册功能和获奖的移动活动应用,让参与者在正确的时间遇到合适的人。
🚀 这个职位
我们正在寻找一位具有自主意识的产品经理,一位将数据视为智能、人工智能驱动系统基础的人,而非数据本身。
Grip 正在构建一个平台,其中人工智能代理代表组织者和参与者行动。要实现这一点,支撑这一层的数据必须准确。这就是这个角色的起点:深入参与数据摄入,理解数据在平台中的流动,并构建干净、结构良好的数据层,这是自主系统所依赖的。
你将参与系统集成、ETL 流水线和 CDP 跟踪工作,不是作为传统的数据管道工作,而是以明确的眼光看待上面的 AI 层需要什么。你会在询问“这些数据是否以代理可以使用的格式存储”之前,先思考“这些数据是否存在”。随着这一基础逐渐成型,你的职责自然扩展到 Grip 的 MCP 设计、自主工作流和 AI 系统架构。
在你自己的工作流程中,自主工具已经是默认选择。你使用 Claude Code、GitHub 自动化和代理来管理你的产出,不是因为被要求这么做,而是因为这就是你的运作方式。
这个职位是基于英国的远程岗位。
🎯 核心职责
构建自主系统的数据层 - 当前重点
· 诊断并解决 Engage 中当前的数据集成挑战,清晰地看到干净的数据如何使下游 AI 功能成为可能。
- 主导数据集成的产品路线图,绘制数据在 Grip 中的流动路径,并根据当前报告需求和未来的自主使用进行塑造。
- 推动与组织者系统、第三方供应商和企业平台的 API 集成工作,始终考虑数据将如何被 AI 系统消费。
- 与数据工程师合作设计 ETL 流水线和数据集结构,思考 AI 代理需要的格式和精度
查看英文原文
🚀 Who are We?
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.
🚀 The Role
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.
🎯 Core Responsibilities
Building the data layer for agentic systems - immediate focus
· 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.
🚀 Your Career Path
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.
🚀 Grip Benefits
- Grip is a remote-first company, but we have an office in London Bridge which you're welcome to use as much as you like
- Company Training Sponsorship Programme
- 25 holiday days per year
- Sabbatical Leave
- Career Progression Pathways — an opportunity to take the lead in shaping an entire industry through AI
- Kind, fun and ambitious company culture
- Group Life Insurance and company health plan
Requirements
🙌 Who You Are
- 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.
Originally posted on Himalayas