AI Product Manager

(#5027) About the Role: AI Product Manager responsible for driving the success of AI products by combining expertise in product management principles with a deep understanding of AI technologies and their applications.We are looking for an AI-savvy Product Manager to join the project programme for our Client. The Engineering team builds and maintains a framework-agnostic UI component library used across Client’s software products, and is now actively embedding AI-assisted workflows, MCP-based agentic infrastructure, and automated SDLC tooling into its engineering practice. In this role you will own the product backlog, define and prioritise the roadmap for AI-enhanced capabilities, align cross-functional stakeholders (engineering, architecture, Client’s PMs), and drive measurable delivery outcomes in a fast-moving agentic tooling context. About the Client: Our Client is the largest engineering company in Europe, and holds the position of global market leader in industrial AI, automation, and industrial software. Become a part of Client’s innovation department which is creating and managing cutting-edge technical architectures, serves as a shared platform for research and development within Client's large organization. It primarily focuses on research and development including broad incorporation of Artificial Intelligence (AI), cloud-based software, high-performance computing, etc. Responsibilities: Product Strategy & Roadmap • Define and maintain the AI product roadmap for the  UI component library product, aligned with Client’s Digital Innovation department’s strategic objectives. • Translate business goals and engineering insights into a prioritised, well-groomed backlog using PMBOK and agile best practices. • Lead quarterly UI component library roadmap reviews with stakeholders and N-iX leadership. AI & Agentic Infrastructure Ownership • Own the product definition for AI-integrated SDLC tooling: issue analysers, GitLab analytics skills, Claude Code agents, MCP server configurations, and automated reporting pipelines. • Work closely with the UI Architect, Engineering Leads to evaluate and prioritise new AI capabilities for integration into the  UI component library development lifecycle. • Define acceptance criteria for agentic features, including observable behaviour, error handling, and handoff points between human and AI agents. Backlog & Delivery Management • Manage and refine a complex backlog spanning UI components, AI tooling, DevOps automation, and platform quality. • Coordinate and execute releases planning and scope management • Aligning on business needs, performing AI-analysis for advancing the prioritization process, ensuring the issues and new features are structured and validated with business stakeholders/consumers. Stakeholder Alignment & Communication • Act as the primary bridge between Client’s product stakeholders and the vendor’s and N-iX’s engineering teams, ensuring clear, timely, and transparent communication. • Produce executive-level product roadmaps reports aligned to Company’s brand guidelines. • Identify, track, and escalate risks and dependencies in the delivery timeline. Consumer & Quality Focus • Maintain the consumer-facing  UI component library roadmap based on user requests and feedback; facilitate correction actions for input requirements from component consumers. • Champion quality gate automation, testing framework improvements, and CI/CD pipeline coverage as product-level acceptance criteria.   Key Skills & Requirements: Product Ownership • 3+ years of experience as a Product Owner or Product Manager in a software engineering environment. • Proven track record of managing complex backlogs with competing priorities across multiple workstreams. • Strong command of agile frameworks (Scrum, Kanban) and PMBOK knowledge areas. AI & Technical Fluency • Working knowledge of AI/LLM-powered tooling - including prompt engineering, agentic workflows, and MCP (Model Context Protocol) concepts. • Ability to define product requirements for AI features without requiring deep ML expertise; comfort working alongside AI infrastructure and agent teams. • Familiarity with modern SDLC automation: CI/CD pipelines, GitLab, automated code review, AI-assisted issue triage, and analytics-driven PM. Stakeholder & Delivery Management • Demonstrated ability to manage enterprise stakeholders in a distributed, multi-vendor delivery model. • Experience translating technical delivery progress into executive-ready communications (status reports, roadmap decks, risk registers). • Data-driven mindset: comfortable with delivery metrics (cycle time, throughput, burndown, eNPS) as inputs to backlog prioritisation. Communication & Documentation • Excellent written and verbal communication in English (business-level required; C1+). • Ability to produce well-structured PRDs, discovery outputs, acceptance criteria, and stakeholder presentations. Nice to have: • Experience with UI platform or design system products (component libraries, Stencil.js, web components). • Familiarity with MCP server architecture, LLM agent orchestration frameworks (LangChain, Semantic Kernel, CrewAI), or agentic infrastructure patterns. • Background working within large enterprise engineering organisations. • Experience using AI-powered PM analytics or GitLab data pipelines for project health reporting. • Proficiency with data visualisation tools (Power BI, Grafana, custom HTML/PDF reports). Certifications: Advantageous • AI Product Management certification (e.g., Pragmatic Institute AI PM, Product School AI PM Certificate) • ITIL 4 Foundation — for service and change management context in enterprise delivery