AI Product Manager – Legal only

London
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist Degree Apprentice within Field Quality Data Scientist Degree Apprentice within Field Quality Apprentices Crewe, GB 6 Feb 2026

Data Scientist KTP Associate - Salford

Data Science Lead

Lead Machine Learning Engineer, AI

Data Science Lead

Principal Data Scientist

Please note: Do not send in your CV if you do not have any recent Legal experience within 2 to 3 years. Hybrid model offers 2 days WFH and 3 days in the office, depending on workload.

Job purpose:

  • A leading international Law Firm organisation is expanding its IT Services team and is seeking an AI Product Manager to take ownership of a dynamic portfolio of AI tools—spanning both internally developed systems and cutting-edge third-party products.

  • This role offers a rare opportunity to influence the AI roadmap within a progressive and fast-paced environment. You’ll work at the intersection of legal tech, AI innovation, and product strategy, helping to shape the digital future of a highly respected sector.

    Skills required:

  • Experience working for a law firm or legal operations (Essential)

  • Proven experience in product management — buying and building applications.

  • Deep understanding of AI technologies: ML, NLP, neural networks

  • Strong project management skills with multitasking ability

  • Exceptional written and verbal communication

  • Analytical mindset with proficiency in data tools

  • Bachelor’s degree in Computer Science, Engineering, Business or related field (advanced degree preferred)

    This position comes with very good benefits and offers a secure, stable and career growth path.

    Be part of the team that’s shaping what’s next in AI and digital innovation

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.