Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead AI Product Manager

Norton Blake
London
7 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist & AI Product Manager

Data Science Lead: AI Product & Scale

Data Scientist – Grid Innovation Model Development

Data Scientist & AI Product Lead

Senior Data Scientist

Senior Data Scientist

Lead AI Product Manager, London/Hybrid, FTC, £100,000 - £110,000 per annum

My client, a leading Fin-Tech company are currently looking for a Lead AI Product Manager on a FTC basis to shape and deliver the clients product to become a market leading cloud-based platform, finding innovative solutions to address client problems.

Main duties

  • Working with clients and their team members to define, shape and solve problems via the product.
  • Working with the Chief Product Officer, you will define and track quarterly objectives, own your ongoing product roadmap and any related metrics or key results.
  • Working with designers, engineers and data scientists to explore, test and document solutions to these problems.
  • Coordinating and coaching cross functional squads to discover solutions to problems and deliver OKRs.
  • Collaborate with Intelligence & Analytics, Engineering and Client teams to embed product releases for maximum impact and value.
  • Working with our QA engineers, you will define repeatable and automated tests for all proposed solutions, so that we deliver performant and high-quality releases.
  • Line management and development of one Junior Product Manager in line with business goals and career progression aspirations.

Requirements

  • Experience as a senior or lead Product Manager, ideally within a scaling fintech or relevant organisation, leading multiple cross functional squads of engineers, designers, and data scientists.
  • Operating in a complex technology and data environment, with a good understanding of data engineering, data science and artificial intelligence.
  • A clear track record of solving the hard problems by bringing cross functional teams together and inspiring your team in the process.
  • Experience of delivering impactful products in an agile manner.
  • Setting up, managing, and getting the best out of Jira, Confluence and Product Analytics tools.
  • You can communicate clearly and effectively to challenging audiences, including to clients and engineers.
  • Experience communicating complex technology solutions in simple terms to non-technical users or stakeholders.
  • Technical requirement definition in a complex B2B environment.

APPLY NOW!

Unlhbi53aGVhdGxleS4yNDI5My4xMjI3MUBub3J0b25ibGFrZS5hcGxpdHJhay5jb20.gif

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.