What you’ll do

Set product direction and make trade-offs. Own the strategy and roadmap for serverless GPU workloads, dedicated capacity, and related compute products, deciding what gets prioritisedand why.
Understand customersand their workloads. Work directly with developers, ML teams,and infrastructure buyers to identify where deployment, scaling, reliability, or cost blocks adoptionand expansion,and use market insights to identify where Runware can win.
Own production trade-offs. Decide how Serverless balances cold starts, performance,and cost with capacity, availability, workload isolation,and governance.
Drive delivery with Engineering and Design. Turn recurring customer needs into requirementsand prototypes, test product flows yourself,and resolve decisions as technical constraints emerge.
Make production use manageable. Shape APIs, SDKs, CLI workflows, documentation,and the platform so developers can deploy, debug,and operate workloads in production without needing help at each step.
Drive commercial outcomes with GTM. Bring customer and workload insights into product positioning, pricing, packaging,and prospect conversations.
Measure outcomesand adapt. Track activation, deployments, production usage, reliability, expansion,and revenue to continuously improve the productand roadmap.
Strong product management experience owning technically complex cloud, infrastructure, platform, compute, or developer infrastructure products from discovery through launch, adoption,and iteration.
Strong understanding of softwareand infrastructure systems,with the technical depth to discuss customer architecturesand product trade-offs across APIs, containers, distributed systems, networking,and storage.
Experience working directly with technical customers, understanding their architecturesand workloads,and translating their needs into scalable product decisions.
Experience building for developersand understanding the journey from a first API call or deployment to dependable production usage.
Strong product judgement,with the ability to prioritise across customer needs, engineering constraints, platform investment,and revenue potential.
Strong ownershipand comfort operating in a fast-moving, ambiguous environment where you’re expected to identify problems, create clarity,and drive work forward.
A hands-on approach: you test products, inspect data, demo to prospects,and use prototypesand AI tools to accelerate discoveryand decisions.
- Nice to have
- Experience with GPU compute or AI infrastructure, including inference, fine-tuning, training, or batch workloads.
- Experience building serverless, cloud compute, Kubernetes, or container-based infrastructure products.
- Strong awareness of the AI infrastructureand cloud compute landscape, including emerging platforms, products,and market trends.
- Previous technical experience in software engineering, infrastructure, DevOps, platform engineering, or a related discipline.
- Experience with usage-based billing, metering, reserved capacity, or infrastructure pricing.
- Experience working with enterprise infrastructure requirements around security, reliability, governance, or capacity.

We’re a remote-first collective, meeting in person twice a year to plan, brainstorm, celebrate wins,and enjoy some face-to-face time. We have core hours for cooperative workingand calls, but outside of that your calendar is yours. Work the hours that let you perform at your peak while also building a healthy life.

Our release cycles are fastand intense, but they’re followed by real downtime. After big pushes we expect the team to unplug, recharge,and come back ready & stronger than ever for the next leap.