AI Senior Product Manager

Manchester
3 days ago
Create job alert

AI Product Lead / Manchester or London / £110,000 + Bonus

We're partnered with a high‑growth, PE‑backed organisation at the forefront of applied AI, who are looking to appoint an AI Product Lead to drive the vision, strategy and delivery of their flagship AI platform.

This is a senior, high‑impact role where you will take ownership of shaping how AI is used to solve complex, real‑world problems for major enterprise clients across regulated and data‑heavy industries. Working closely with the Chief Product Officer, you'll play a pivotal role in defining product direction, bringing structure to discovery and delivery, and converting AI capability into production‑ready, revenue‑generating products.

The business is scaling rapidly, with a strong customer pipeline and significant investment. This role suits someone who thrives in fast‑paced startup/scale‑up environments and enjoys full ownership, from defining the problem, to prototyping, through to shipping features into production.

If you're motivated by building AI products that have tangible commercial and user impact, this is the opportunity to take something with huge potential and lead it into its next phase of growth.

What do we need from you?

Proven experience delivering AI‑led or ML‑driven products into production (not just discovery or concept).
Examples of taking product features from customer need → prototype → shipped product in real customer environments.
Experience working in startup or scale‑up businesses (Seed → Series A-D ideal), where speed, adaptability and hands‑on ownership are essential.
Ability to define and own a product vision, build roadmaps, prioritise effectively and bring structure to delivery.
Background operating as a Product Lead / Senior Product Manager, influencing strategy while still being close enough to delivery to drive outcomes.
Strong problem‑solving skills with a track record of turning complex challenges into clear, deliverable product solutions.

The Role

As AI Product Lead, you will own the strategy, roadmap and delivery of a next‑generation AI product used to automate, interpret and solve complex information‑rich workflows for enterprise clients.

You'll work closely with the CPO and founding team to establish a disciplined product function while maintaining the creative, fast‑moving pace of a scale‑up.

This is a hands‑on strategic role: you'll shape the vision, validate customer problems, develop prototypes, and lead the delivery of features into production environments.

Key Focus Areas

Product Ownership & Vision

Define and deliver the AI product roadmap aligned to commercial strategy
Establish product discipline, structure and processes within a scaling organisation
Translate customer and market needs into clear product requirementsAI‑Led Product Development

Lead the creation and delivery of AI features, ensuring models, workflows and outputs reach production
Partner with engineering and data science teams to convert capability into usable customer experiences
Ensure product decisions are driven by insight, experimentation and measurable outcomesHands‑On Delivery & Execution

Work closely with the CPO to drive feature delivery from concept to launch
Own prototyping, hypothesis testing and iterative development
Take responsibility for shipping features, not just defining themCustomer & Market Impact

Engage directly with enterprise customers to validate use cases and gather feedback
Prioritise features based on customer value, revenue impact and AI feasibility
Support go‑to‑market planning and readiness

What's on Offer?

Up to £110,000 salary
Opportunity to take ownership of a high‑growth AI product in a PE‑backed scale-up
Build and lead the next evolution of the product function
Work directly with a highly credible CPO and founding team
Shape and ship AI products used by major enterprise clients
Ability to make a visible impact in a business scaling rapidly
Hybrid - 1-2x a monthWhy Join?

This is a rare chance to take charge of an AI product with huge market potential and move it from founder‑led to product‑led.
You'll own the future direction of the product, work with cutting‑edge AI capabilities, and play a critical role in driving commercial value.
If you thrive in environments where you can combine strategic ownership with hands‑on delivery, this role gives you the platform to build something with real impact.

If you're interested in learning more, please apply or send your CV over to Dominic Brown - with a time to discuss the opportunity in more detail

Related Jobs

View all jobs

Senior Delivery & Product Lead (AI/IoT)

Senior Software Engineer

Senior Software Engineer

Embedded IoT / Edge Solutions Sales Representative, Manager and Director

IoT Solutions Architecture Manager (Americas only)

IoT Solutions Architecture Manager (Americas only)

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 Edge Computing Tools Do You Need to Know to Get an Edge Computing Job?

If you’re trying to start or grow a career in edge computing, it can feel like you’re navigating a maze of tools, frameworks and platforms — Kubernetes, Docker, IoT frameworks, AWS Greengrass, Azure IoT Edge, OpenShift, TinyML toolkits, networking orchestration, real-time streaming frameworks, and on it goes. Scroll job boards and community forums and it’s easy to conclude that unless you master every buzzword imaginable, you’ll never get a job. Here’s the honest truth most edge computing hiring managers won’t necessarily say out loud: 👉 They don’t hire you because you know every edge computing tool — they hire you because you can solve real system problems using the tools you know. Tools matter, yes — but only when they support clear outcomes: reliable systems, performance at scale, secure edge deployments and real business value. So how many edge computing tools do you actually need to know to secure a job? For most edge computing roles, the answer is fewer than you think — and a lot clearer when sorted by fundamentals and roles. This guide shows you what matters, what doesn’t, and how to focus your time wisely so you come across as capable, confident and employable.

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

In today’s fast-evolving tech landscape, edge computing is one of the most sought-after fields — blending distributed systems, embedded systems, networking, cloud, IoT, data and real-time processing. But that also means hiring managers are highly selective. They scan applications fast and look for signals of relevance, impact, technical depth and real-world delivery long before they read every line. This guide demystifies what hiring managers in edge computing look for first in your application — so you can tailor your CV, portfolio and cover letter to jump out of the stack. Whether you’re targeting edge systems roles, embedded IoT edge jobs, edge-native data roles, edge platform engineering or edge-AI positions, this checklist will help you position your experience in a way hiring managers can trust immediately.

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

Edge computing is rapidly moving from niche concept to critical infrastructure. As organisations deploy connected devices, sensors, autonomous systems and real-time analytics, processing data closer to where it is generated has become essential. From smart cities and manufacturing to healthcare, transport, defence and telecommunications, edge computing underpins systems where latency, reliability and resilience matter. Demand for edge computing skills across the UK is rising steadily — yet employers consistently report difficulty finding candidates who are genuinely job-ready. Despite growing interest and academic coverage, universities are not fully preparing graduates for real edge computing jobs. This article explores the edge computing skills gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build sustainable careers in edge computing.