Technical Product Manager - AI Compute Platform
Our partner is looking for a Technical Product Manager - AI Compute Platform based in Spain.
In this role, you will help shape and scale a next-generation AI cloud platform powering some of the most demanding machine learning workloads in the world. This is a deeply technical product management role where you will collaborate as a peer with senior engineers on topics such as GPU orchestration, distributed training, cluster operations, and cloud APIs. You will translate complex customer needs into robust platform capabilities that enable large-scale AI training and inference. Own end-to-end product strategy, roadmap, and execution for a critical slice of an AI compute platform, ensuring alignment with customer and business outcomes.
Define and evolve platform contracts such as APIs, system behaviors, lifecycle semantics, and developer-facing interfaces at hyperscaler quality.
Lead cross-functional execution across engineering, SRE, networking, storage, observability, IAM, billing, capacity planning, and customer-facing teams.
Drive structured product discovery through customer interviews, usage analytics, incident analysis, and support feedback loops.
Collaborate as a technical peer with engineering teams to evaluate architecture decisions, system trade-offs, and platform design quality.
Own adoption and performance of shipped features, ensuring continuous improvement based on real-world usage and telemetry.
6+ years of experience in Product Management, Platform/Product Infrastructure roles, or equivalent experience in SRE or Engineering leadership with strong product ownership.




~ Strong technical foundation in cloud infrastructure, distributed systems, or AI/ML platforms, with the ability to reason about system design and architecture.
~ Experience working with or operating large-scale infrastructure such as GPU clusters, HPC systems, or multi-tenant cloud environments.
~ Proven track record of shipping complex technical products with measurable impact on customers or platform performance.
~ Strong analytical skills with experience defining metrics, working with telemetry, and driving data-informed product decisions.
~ Experience leading discovery processes, including customer interviews, usage analysis, and support-driven insights.
~ Ability to engage confidently with engineering teams on topics such as API design, system reliability, control planes, and distributed systems behavior.
~ Excellent communication and stakeholder management skills across engineering, product, operations, and executive teams.
~ Familiarity with GPU infrastructure, Kubernetes, Slurm, or HPC environments is highly desirable.
~ Experience with distributed ML training or inference workloads (e.g., multi-node training, NCCL, checkpointing, fault-tolerant systems) is a strong plus.
~ Exposure to cloud platforms at hyperscaler scale (AWS, GCP, Azure) and developer experience design (APIs, CLI tools, observability systems) is advantageous.
~ Opportunity to shape foundational infrastructure for the general AI ecosystem.
~ Flexible, trust-based work environment with strong autonomy.
~ Opportunity to work on problems at the frontier of cloud infrastructure and AI compute.

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