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Описание: |
Windmill is a boutique digital product delivery company. Our global team of designers, strategists, and engineers are passionate about creating impactful, elegant, and functional digital products. Since 2012, we’ve helped organizations in complex industries—such as banking, finance, healthcare, and compliance—solve real-world challenges and unlock new opportunities.
We are headquartered in Switzerland, with team members across the UK, USA, Portugal, Ukraine, and India. We celebrate and seek diversity, inclusion, and collaboration in everything we do.
Learn more at www.windmillsmartsolutions.com
About the role
We’re building high-assurance, multi-agent AI products that our customers can trust with real work and real data. As AI Product Owner (AIPO), you own the definition of value for your domain: you decide what we build and why, and ensure every behaviour we ship traces back to a validated user need, a business KPI, and a clearly documented specification in our contract-driven delivery model.
Reporting to the [Head of AI Product / CPO], you’ll work closely with AI Architecture, Engineering, Platform & Security, and Verification to turn ideas into safe, reliable, and measurable outcomes.
Key responsibilities
* Own the Base Specification for your product domain: goals, user stories, acceptance & exception criteria, non-functional requirements (NFRs), and KPIs.
* Build and evolve the Value Traceability Matrix that links user stories → Contract endpoints / events → tests → KPIs, ensuring line-of-sight from requirements to code and outcomes.
* Prioritise and manage epics, increments, and backlogs for multi-agent AI features, balancing user value, risk, and technical constraints.
* Shape agentic workflows: collaborate with AI Lead and Tech Lead to define how user intents turn into plans, tool calls, and responses, and where guardrails, approvals, or explanations are required.
* Lead discovery & validation: run user interviews, workshops, and experiments to deeply understand user problems and validate solutions before and after shipping.
* Partner on AI metrics and evaluations: work with AI Lead, Data, and Verification to define AI-specific metrics (e.g. task success rate, safe-response rate, human intervention rate) and connect them to business KPIs.
* Collaborate with AI Lead, Tech Lead, Platform & Security, and Verification to align scope, Contracts, quality expectations, and release criteria.
* Drive stakeholder communication: maintain a clear roadmap, communicate priorities, trade-offs, and risks, and report KPI performance for your area.
* Champion evidence-based decisions using experimentation, usage data, AI evaluation results, and feedback from customers and internal users.
* Ensure robust Definitions of Ready and Done: every backlog item is spec’d, mapped to Contracts and tests, and backed by evidence (test results, evals, documentation) at release time.
Requirements
* Proven experience as a Product Owner / Product Manager, ideally in AI, data, or developer/technical products.
* Strong ability to write clear user stories, acceptance criteria, exception scenarios, and NFRs.
* Comfortable working with APIs, basic data models, and technical specs (you don’t need to code, but you can read and discuss Contracts with engineers).
* Experience with KPI-driven roadmapping and experimentation (e.g. A/B tests, feature flags, iterative rollout).
* Excellent communication and stakeholder management skills; able to align diverse technical and non-technical stakeholders.
* Structured, outcome-oriented mindset and a bias towards clarity, evidence, and iteration over opinions.
Nice to have
* Experience with LLM-based products (copilots, chatbots, agents) or data-heavy products.
* Exposure to high-assurance / regulated domains (e.g. finance, healthcare, safety-critical systems).
* Familiarity with product and analytics tools (e.g. Jira/Linear, Figma, Amplitude/Mixpanel, experimentation platforms).
What success looks like
Within 6–12 months in the role, you will have:
* Delivered features that show high goal-completion and adoption against your key KPIs in your domain.
* Established a clear KPI tree and Value Traceability Matrix so that requirements, Contracts, tests, and business outcomes are visibly linked.
* Reduced “scope confusion” and rework in delivery: engineering and verification teams report high clarity and stability of requirements.
* Demonstrated improving AI and product metrics over time (e.g. higher task success rate, lower manual interventions, improved user satisfaction).
* Built strong relationships with stakeholders, who describe you as a trusted partner for clarity, transparency, and outcome-focused decision-making.
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