Product Lead - Serverless & Compute

This role owns the direction and commercial results for serverless and dedicated GPU compute products. A strong candidate has run technically complex cloud or infrastructure products from discovery through launch and growth, and can talk through customer architectures and trade-offs in APIs, containers, distributed systems, networking and storage. It also calls for direct work with developer and infrastructure buyers, turning recurring production problems into products and measurable adoption.

How it fits the AI era

The product itself serves teams running AI workloads, so the work sits close to how inference and training get deployed and scaled. AI tools help with discovery, prototyping and testing flows, but the hard calls on cold starts, cost, capacity and reliability stay with a person who understands the systems. Judgement about which customer problems are worth building for remains human.

How it builds AI experience

Working here means learning the practical side of GPU inference and compute: how workloads behave at scale, what serverless trade-offs cost, and how usage based pricing and capacity planning work. That knowledge builds through direct customer conversations, hands on testing of APIs and SDKs, and reading production data. Prior exposure to GPU compute, Kubernetes or container platforms helps, and the posting treats it as a strong plus rather than a requirement.

Worth showing

• Infrastructure product ownership
• Developer platform launches
• Customer discovery with engineers
• Usage based pricing

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Runware

High-performance inference platform providing serverless and dedicated GPU infrastructure across thousands of machine learning models.