Germany | Hybrid from Heidelberg | €90,000–€100,000 base + performance incentives
You’ll own the product that decides where and when AI workloads run.
This is a chance to take ownership of an AI Scheduling product at a growing AI infrastructure business. You’ll define the multi-year product vision, decide what gets built and work directly with engineers, infrastructure teams and enterprise customers to solve the challenges of running AI at scale.
The product sits around some of the hardest practical problems in AI infrastructure: how jobs are queued, how expensive GPU resources are allocated, and how latency, reliability and performance are managed as workloads grow.
You’ll have real ownership. Rather than managing a quarterly backlog, you’ll shape the longer-term direction of the product, turn customer problems into clear product decisions and work closely with leadership and engineering to get those decisions into production.
You’ll also have direct customer exposure, giving you the opportunity to understand how organisations are actually using AI infrastructure and feed those insights back into the product roadmap.
This could suit you if you’re already a Technical Product Manager working on cloud infrastructure, platforms, developer tooling or cluster management and want to take ownership of a product at the centre of the AI infrastructure market.
You’ll need:
- 5+ years of Product Management experience, including ownership of infrastructure, platform or developer tooling products
- Experience with technologies such as Kubernetes, OpenStack, Slurm, VMware or similar
- A good understanding of cloud, compute infrastructure and how AI/ML workloads are run
- Experience creating longer-term product roadmaps and working closely with engineers and technical customers
- A technical background through education or hands-on experience
You’ll be based in Germany and able to work from the Heidelberg office on a hybrid basis, with up to 30% travel between Germany and the US.
If you’re interested in owning a product that sits at the intersection of AI, infrastructure and resource management, I’d be happy to tell you more.
