Senior AI - first Product Owner

We are looking for a Senior Product Owner who combines strong delivery experience with a genuine, hands-on approach to AI-assisted requirements and analysis work. You will work across varied client engagements - from discovery and requirements elicitation to backlog management and stakeholder alignment - and are expected to contribute (practice not theory). The ideal candidate has built a real, personalized AI workflow for BA/PO tasks (using agents/self-developed skills for research, drafting, analysis, and documentation) and continues to refine it. Single-prompt ChatGPT usage is not sufficient for this role. This is a hybrid role, which means we'd like you to work in the office occasionally, especially during client visits or other important company meetings. Responsibilities • Own requirements end-to-end: discovery, elicitation, analysis, documentation, validation, and acceptance • Manage product backlogs, prioritise work, and coordinate with engineering and design teams • Work directly with clients in English - elicit requirements, manage expectations, present deliverables, navigate competing priorities • Produce structured context documentation (domain rules, stakeholder decisions, technical constraints, edge cases) usable by both team members and AI tools that AI agents consume to generate artefacts • Design agent workflows for recurring BA/PO tasks: define inputs, instructions/skills, execution sequence, outputs, and quality gates at each step • Run multiple agent-assisted workstreams in parallel and integrate outputs across them • Validate agent output • Continuously improve prompts, context structures, and agent workflows based on what works and fails in actual delivery • Contribute to the team's AI-first delivery methodology: context templates, workflow patterns, prompt libraries, and validation frameworks Requirements • 5+ years as a Business Analyst, Product Owner, Product Manager, or equivalent in software delivery • Active daily use of AI tools (LLMs, coding assistants, or similar) in professional delivery work - with specific workflows or practices you can demonstrate, beyond single-prompt usage • Understanding of how LLMs and AI agents work: what context they need, how they execute multi-step tasks, where they fail, and why output validation matters • Strong structured writing: clear documentation, well-organised specs, templates and frameworks that both humans and agents can follow • Working experience with engineering teams: ability to read technical documentation, discuss system constraints, write actionable requirements • Client-facing delivery experience: comfortable leading workshops, managing expectations, and presenting to senior stakeholders • Familiarity with Agile delivery practices (Scrum, Kanban) and standard BA/PO tooling (Jira, Confluence, Miro, or similar) • Clear communication skills in English (B2+), both written and spoken