Staff Product Manager, Compute Platform

JobgetherBrussels (Firmensitz, recherchiert)Job.bopublished 10/12/2026
Must-have:KubernetesCloudAIHealthTechLeadRemote

Accountabilities Own product strategy and roadmap: Define and execute the vision for managed application hosting, serverless functions, and container registry services, translating platform strategy into prioritized features that balance simplicity, performance, and operating efficiency.

Drive platform economics: Determine how applications, functions, and registry workloads use shared compute infrastructure. Partner with engineering and finance to improve utilization, workload density, resource allocation, and cost per unit of customer usage.

Anticipate infrastructure trends: Track processor roadmaps, including Intel, AMD, and ARM; virtualization and microVM technologies; container runtimes; and workload isolation models. Translate emerging developments into product decisions around instance sizing, runtime selection, and price-performance tiers.

Improve the developer journey: Own the end-to-end experience from source code or container image through deployment, autoscaling, and observability. Identify and remove friction across authentication, networking, registries, logs, and billing.

Lead customer discovery: Engage developers, startups, and small-to-medium-sized business platform teams. Analyze support cases and community feedback to identify customer needs and translate them into jobs-to-be-done, user stories, and acceptance criteria.

Own packaging and pricing: Develop pricing and metering models for compute, network egress, build minutes, storage, function invocations, and image pulls. Ensure pricing reflects cost to serve while identifying opportunities to increase adoption and cross-product usage.

Guide technical product decisions: Collaborate with engineering on control-plane and data-plane architecture, build pipelines, scheduling, autoscaling, serverless cold starts and concurrency, registry performance, garbage collection, and multi-region placement.

Improve reliability and performance: Establish and monitor service-level objectives (SLOs), performance standards, and cost targets. Prioritize improvements that strengthen availability, deployment success, latency, and infrastructure efficiency.

Monitor the competitive landscape: Assess competing managed compute, platform-as-a-service, serverless, and container solutions to identify opportunities to differentiate through simplicity, performance, and pricing.

Lead product launches and adoption: Coordinate launches with product marketing, documentation, sales, and support teams. Remain accountable after general availability for activation, adoption, retention, expansion, and gross margin.

Measure business and product outcomes: Track service revenue, attach rates, infrastructure utilization, cost per workload, gross margin, time to first deployment, customer retention, deployment reliability, function cold-start latency, and image-pull performance.

Collaborate across teams and regions: Work closely with engineering, infrastructure, finance, and go-to-market stakeholders across time zones, contributing to the development of the compute platform product management function.

Requirements

Product management experience: At least 8 years of product management experience, with a demonstrated record of defining and launching managed cloud compute, platform-as-a-service (PaaS), serverless, or container products. Experience owning both customer-facing functionality and unit economics is especially valuable.

Cloud platform knowledge: Strong understanding of PaaS, serverless computing, and container registry models, including buildpack-based deployments, function runtimes and triggers, concurrency, cold-start trade-offs, and OCI image building, storage, and distribution.

Compute infrastructure fluency: Solid knowledge of cloud compute technologies, including Intel, AMD, and ARM processor architectures, virtualization and microVMs, container runtimes, and isolation models. Ability to understand how infrastructure choices affect workload density, latency, reliability, and cost.

Cost and capacity management: Experience analyzing compute, memory, storage, and networking cost drivers, developing cost-to-serve models for multi-tenant services, and translating financial and capacity insights into pricing and utilization targets.

Developer experience expertise: Strong instincts for creating intuitive developer products, with the ability to specify APIs, command-line interfaces, and console workflows that offer useful defaults without unnecessarily restricting advanced users.

Data-driven decision-making: Ability to define meaningful product metrics, interpret utilization and margin dashboards alongside customer and product analytics, and adjust strategy based on measurable results.

Technical and commercial judgment: Comfort balancing architecture decisions, customer experience, infrastructure efficiency, pricing, and profitability when making product trade-offs.

Cross-functional leadership: Excellent communication and stakeholder management skills, with experience aligning engineering, infrastructure, finance, and go-to-market teams across different locations and time zones.

Preferred Kubernetes experience: Hands-on familiarity with Kubernetes operations, workload scheduling, operators, Helm, or building products on top of Kubernetes.

Preferred infrastructure experience: Background in IaaS or compute products, such as virtual machines, bare-metal services, capacity planning, or fleet efficiency.

Preferred competitive product experience: Experience building, launching, or competing with services such as Heroku, Render, Fly.io, Cloud Run, Lambda, Fargate, ECR, GCR, ACR, or comparable platforms.

Additional preferred qualifications: Familiarity with data center fundamentals, such as rack layouts, power and cooling, and network design; experience leading a product area in a new geography; or knowledge of an established cloud product portfolio.

Location and work authorization: This is a remote role in the United States, with the requirement that candidates be located within or willing to relocate to within 60 miles of one of the designated hiring locations. Applicants should confirm their eligibility to work in the United States and any applicable sponsorship requirements.

Benefits

Compensation: Annual salary range of $186,400–$279,600 , based on relevant experience, skills, and market factors.

Additional compensation: Potential eligibility for a performance-based bonus and equity compensation, including grants upon hire for eligible employees.

Employee stock purchase plan: Eligible employees may participate in an employee stock purchase program.

Remote work: Remote working arrangement, subject to the specified location requirements.

Flexible time off: Flexible time-off policy.

Well-being support: Access to an Employee Assistance Program and employee meetups.

Career development: Reimbursement for relevant conferences, training, and education, along with access to LinkedIn Learning’s extensive course library.

Professional growth: Opportunity to work with experienced technology professionals, influence cloud platform strategy, and contribute to products used by developers and businesses.

Location-specific benefits: Additional benefits are provided according to local regulations and employee needs; specific healthcare and other benefit details may vary by location.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1