Product Owner AI - Manchester Hybrid

Product Owner (AI) - Manchester Hybrid Salary : £55,000About the Role

We are seeking a Product Owner with a strong focus on AI/ML products who thrives in dynamic, fast-paced environments and enjoys working closely with small, high-impact teams. You will lead initiatives involving AI-driven system upgrades, data platform modernization, and greenfield builds, collaborating directly with director-level stakeholders to align technical innovation with business outcomes. Your work will help shape intelligent solutions that drive measurable value through automation, personalization, and data insights.

Key Responsibilities

• Own and manage the product backlog with a focus on AI/ML feature development, turning business needs into actionable user stories and clear acceptance criteria.
• Lead end-to-end initiatives involving AI-powered applications, from data ingestion and model deployment to user-facing functionality.
• Collaborate with data scientists, ML engineers, and software developers to align technical execution with business goals.
• Partner with director-level stakeholders to understand strategic AI objectives, prioritize use cases, and gain buy-in for roadmap decisions.
• Work closely with UX and QA teams to ensure AI features are intuitive, ethical, and deliver high-quality user experiences.
• Ensure timely delivery in a fast-paced agile environment, adapting priorities to emerging AI trends and user feedback.
• Define and track AI-specific KPIs such as model accuracy, precision/recall, and business impact metrics.
• Act as the voice of the customer, advocating for responsible AI adoption and transparency across the product lifecycle.

Skills & Experience

• Proven experience as a Product Owner (or similar role) working on AI/ML or data-driven products in agile/scrum teams.
• Demonstrated success leading AI product development, including model integrations, intelligent workflows, or predictive analytics.
• Strong ability to translate complex AI concepts into business language for executive stakeholders.
• Experience working with data scientists, ML engineers, or AI research teams.
• Familiarity with AI tools and technologies (e.g., model training pipelines, cloud ML services, LLMs).
• Ability to thrive in fast-paced, evolving environments, balancing short-term delivery with scalable AI strategy.
• Strong backlog management, prioritization, and decision-making skills, especially around AI technical trade-offs.
• Technical aptitude with a solid understanding of how AI systems are built, trained, and deployed.

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