We're looking for a Senior Capacity Engineer to own capacity planning across our Compute platforms and services. You'll forecast demand, model infrastructure growth, identify efficiency opportunities, and work directly with engineering, finance, and leadership to ensure we have the right resources in the right place at the right time. A key part of this role is leveraging AI to build intelligent dashboards and drive predictive analysis - moving capacity planning from reactive to proactive. This role sits at the intersection of infrastructure engineering, data analysis, and strategic planning - and operates at a scale few organizations in the world can offer.
Description
- Own the end-to-end capacity planning lifecycle for our platforms - demand forecasting, supply planning, utilization analysis, and efficiency optimization
- Drive monthly capacity forecasts - own the process end-to-end, ensuring timely and accurate submissions every cycle
- Submit and track incremental capacity requests - ensure new resource needs are captured, justified, and filed on a monthly cadence
- Represent the platform in all capacity-related forums and meetings - be the authoritative voice on current state, projected needs, and risks across cross-functional reviews
- Build and maintain capacity models that translate business growth signals into infrastructure requirements
- Use AI to build dashboards and reporting tools that surface capacity health, trends, and anomalies - making complex infrastructure data accessible to engineering and leadership
- Apply AI-driven analysis to predict resource needs and flag capacity risks before they become incidents - shifting the team from reactive firefighting to proactive planning
- Partner with service teams to understand workload characteristics, growth trajectories, and resource consumption patterns
- Identify and drive efficiency improvements - right-sizing, bin-packing, rebalancing, and decommissioning underutilized resources
- Establish and track capacity-related SLOs and KPIs (utilization targets, lead times, headroom thresholds)
- Represent capacity planning in procurement and budget cycles, providing data-driven recommendations for hardware acquisition
- Drive quarterly and annual capacity reviews, surfacing risks and opportunities to senior leadership
Minimum Qualifications
8+ years of experience in infrastructure engineering, capacity planning, SRE, or a related discipline
Experience with capacity planning at hyperscale or large enterprise infrastructure
Demonstrated experience forecasting infrastructure demand and translating it into actionable supply plans
Strong analytical skills - comfortable working with large datasets, building models, and drawing conclusions from utilization and performance data
Experience applying AI/ML techniques to operational or infrastructure problems - anomaly detection, demand forecasting, trend analysis, or similar
Ability to build AI-assisted dashboards and tooling that turn raw infrastructure data into actionable insights
Solid understanding of compute infrastructure concepts: virtualization, containers, orchestration (Kubernetes), bare metal, resource scheduling
Ability to communicate complex technical trade-offs to both engineering teams and non-technical stakeholders
Self-directed and comfortable operating with ambiguity - you define the process, not just follow it
Preferred Qualifications
Hands-on experience with LLMs, AI coding assistants, or generative AI for engineering productivity
Familiarity with infrastructure procurement and hardware lifecycle management
Exposure to time-series forecasting methods (statistical or ML-based)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: 5fcc967b9c84cbe781d32e0ce07f516f
- Posted 9 hours ago
