Senior Product Manager - Data & AI

About this role

Ohme is on a mission to accelerate the global transition to clean, affordable energy. We do that by serving as an integrated hardware and software smart-grid platform, focused on the residential EV charging market.

The worlds of energy, transport and artificial intelligence are colliding and Ohme is at the heart of this new era. By using technology and data integrations to connect cars, chargers, people, energy providers and more, Ohme has a powerful platform that puts the consumer at the core.

Ohme has been selling its chargers to consumers since mid 2019 and has had exponential growth since. We are now operating in multiple countries and have partnerships with the likes of VW, Mercedes, Octopus Energy, and other innovative brands.

We are scaling up the business and are building out the team for rapid growth. If you’re interested joining a fast-growing cleantech venture on a data and AI-first journey to speed up the global transition to clean, affordable energy, read on!

We are looking for a Senior Product Manager, Data & AI to own how Ohme turns its data and AI capabilities into products that deliver real value for customers and the business. You'll own the roadmap for our applied AI and data products, take direct ownership of several of them end-to-end, and partner closely with our teams to ship and iterate at pace.

Ohme's AI is already live with internal and external users, our data platform underpins everything from EV charging to energy trading, and the pace of change is fast. This role is for a product leader who can bring structure to ambiguity, make sharp prioritisation calls, and connect deep technical work to measurable outcomes.

You will work from our London office 3 days a week.

Responsibilities

Product Strategy & Roadmap

• Shape and own the roadmap for Ohme's data and AI products — translating a fast-moving strategy into clear, prioritised plans — and take full end-to-end ownership of specific product areas.

• Translate business and internal teams’ needs into clear, prioritised product requirements and outcomes.

• Make evidence-based prioritisation calls, balancing quick wins against longer-term platform investment.

• Partner with other engineering teams and senior leadership to align the data and AI product roadmap with company strategy.

• Define and track success metrics, holding the team accountable to measurable impact rather than output.

Delivery & Execution

• Work hands-on with AI engineers, ML engineers, data engineers and data scientists to ship products from concept to production.

• Own the backlog, write clear specifications and user stories, and drive planning and delivery cadence.

• Make pragmatic trade-offs on scope, quality and timing to keep delivery moving.

• Turn live production usage and feedback into the loop that shapes what gets built next.