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For Companies At a Glance
- Tasks: Lead AI product initiatives and optimise existing products for publishing.
- Company: Join a fast-moving organisation at the forefront of AI transformation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Shape the future of AI in publishing and drive real impact.
- Qualifications: Experience in tech environments, agile methodologies, and strong communication skills.
- Other info: Dynamic role with a focus on innovation and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
About the Role
As AI Product Manager, you will be a key member of the AI leadership team, working alongside the Director of AI Transformation to deliver our vision for publishing, implementing cost savings and revenue growth. You will manage both new AI product initiatives and the ongoing delivery and optimisation of existing AI products. You will own the roadmap, prioritisation, MVP releases, experimentation with A/B tests, feature releases and sprint coordination. You will work closely with engineering, data, product design, delivery and content operations teams to turn strategic intent into working solutions.
Key Responsibilities
- Lead and execute the Publishing AI vision: define, manage and deliver AI-enabled publishing product features that align with the organisation's strategic goals.
- Work with the Director of AI Transformation and senior leadership to translate the strategy into product roadmaps, epics, MVP launches and feature releases.
- Gather requirements from stakeholders (editorial and publishing teams) and convert them into epics, user stories and detailed requirements in Jira.
- Work with the AI transformation team and Delivery to prioritise requirements (using story points, business value, cost/effort) and maintain the backlog in Jira.
- Coordinate sprints and allocate resources, manage dependencies, risks, and cross-functional teams (engineering, QA, data, design).
- Write and maintain product epics, features, user stories and acceptance criteria; create Jira tickets for development tasks and track progress.
- Drive experimentation: design and manage A/B tests, define success metrics, analyse results, iterate the product.
- Manage full product lifecycle: planning, development, release, maintenance and continuous improvement of AI products.
- Maintain and enhance existing AI products, prioritise enhancements, ensure service stability, realise cost savings and revenue outcomes.
- Understand the capabilities and limitations of AI/ML technologies; identify opportunities for automation, efficiency gains and innovation.
- Monitor product performance and business KPIs, produce insights and recommendations for next phases.
- Serve as the "voice of AI product" internally: communicate vision, status updates, roadmaps, trade-offs and next steps to stakeholders across the organisation.
Job Requirements
- Proven experience in a technology/software environment; preferably with experience delivering digital products in an agile environment.
- Demonstrable experience working with agile teams: writing epics, managing backlogs, writing user stories, working in Jira (or similar) and using story points for prioritisation.
- Experience coordinating sprints, managing resources, dependencies, multi-disciplinary teams (engineering + data + design + operations).
- Strong ability to gather and translate business requirements into technical scope, epics and stories.
- Experience of experimentation/A/B testing, analysing results and iterating based on data.
- Good understanding of AI, machine learning concepts and what is feasible in that domain—able to identify where AI can deliver efficiencies and revenue growth.
- Strong strategic mindset, able to translate vision into roadmap and feature-level deliverables.
- Excellent communication skills: able to engage technical and non-technical stakeholders, influence decisions, clarify trade-offs.
- Strong analytical skills and comfort working with data to drive decisions.
- Familiarity with product metrics, success criteria, KPIs, usage/engagement metrics (especially for AI-enabled products).
- Excellent organisational and prioritisation skills: able to juggle multiple streams of work, shifting priorities, resource constraints.
Desired / Plus Skills
- Experience in product management of AI/ML products or data-driven solutions.
- Experience in publishing, content operations, media or related domain.
- Proven track record of driving cost-savings and/or revenue growth via product initiatives.
- Experience working with cloud platforms, model deployment pipelines.
- Understanding of ethical AI, model risk, bias mitigation.
- Knowledge of sports media, sports betting and affiliate content.
What We Offer
The opportunity to shape the AI transformation roadmap of a fast-moving organisation.
Product Manager – AI Transformation in London employer: Igbaffiliate
Contact Detail:
Igbaffiliate Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Product Manager – AI Transformation in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to AI product management. Use the STAR method (Situation, Task, Action, Result) to structure your answers and showcase your experience effectively.
✨Tip Number 3
Showcase your passion for AI and product management during interviews. Share your insights on current trends, challenges, and innovations in the field. This will demonstrate your commitment and knowledge, making you stand out.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Product Manager – AI Transformation in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI products and agile methodologies. We want to see how your skills align with our vision for AI transformation!
Showcase Your Achievements: Don’t just list your responsibilities; share specific examples of how you’ve driven cost savings or revenue growth in previous roles. We love seeing quantifiable results that demonstrate your impact!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use bullet points where possible to make it easy for us to read through your experiences and skills.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role promptly!
How to prepare for a job interview at Igbaffiliate
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and machine learning concepts. Be ready to discuss how these technologies can drive efficiencies and revenue growth, as well as their limitations. This will show that you understand the landscape and can identify opportunities for innovation.
✨Master the Agile Methodology
Since this role involves working in an agile environment, be prepared to talk about your experience with writing epics, managing backlogs, and coordinating sprints. Familiarise yourself with Jira or similar tools, and think of examples where you've successfully managed multi-disciplinary teams.
✨Bring Data to the Table
You’ll need to demonstrate strong analytical skills, so come equipped with examples of how you've used data to drive decisions. Discuss any A/B testing you've conducted, the metrics you tracked, and how you iterated based on results. This will highlight your ability to manage the full product lifecycle effectively.
✨Communicate Like a Pro
Excellent communication skills are key for this role. Prepare to explain complex ideas in simple terms, especially when discussing trade-offs and roadmaps. Think of scenarios where you've engaged both technical and non-technical stakeholders, and how you influenced decisions through clear communication.
