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Principal Product Manager (London / Dublin / Prague)
LondonSource: WhatJobs
See advert for pay
Overview
In this Principal Product Manager role, you own the end-to-end opportunity behind Spark, an AI-first agentic product for product teams. You shape the roadmap for AI insights, define data and retrieval flows, and drive deployment of reliable, actionable outputs that help product leaders make decisions. You collaborate closely with the founders to tackle hard problems, translate signals into decisions, and elevate the overall user experience with interactive, artifact-like results. This role targets ambitious, enterprise-focused PMs who want to lead a category-defining AI product at scale.
Pay / Benefits
Stock options
MacBook + 34″ monitor
Work from home stipend
5 weeks vacation + 9 sick days
Flexible working hours
Budget for courses, books, conferences
Responsibilities
Understand customer needs and prioritize questions modern product organizations require
Own the AI Insights roadmap: strategy, metrics, and prioritization of the questions Spark answers first
Define data, context, and data flow for Spark to answer reliably, including data model, retrieval, and agent harness
Design agent behavior and answer presentation (conversational, structured, visual, interactive) and drive the shift from simple text to rich artifacts
Own quality and evals: define evaluation criteria for answers, insights, and artifacts; monitor releases for improvement
Anticipate AI frontier developments and articulate capabilities/limits to GTM teams
Prototype in code using AI tools to validate concepts with customers
Mentor other PMs on AI product craft and drive end-to-end ownership of outcomes
Collaborate with founders and cross-functional partners to align on product vision and execution
Key requirements
8+ years in product management, hands-on, enterprise B2B SaaS
Extensive experience shipping AI/LLM-powered products in production
Deep expertise in designing agentic AI products with planning, tool use, and multi-step actions
Experience owning data and retrieval pipelines behind an AI product
Experience building evaluation frameworks (offline/online) and using prompts and evals to drive decisions
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