GEICO
Staff Engineer – Capacity Planning and Management
Job Description
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers. GEICO is seeking a Staff Engineer – Capacity Engineering to support the buildout of core capabilities within our Capacity Management Platform. This platform is essential for enabling proactive infrastructure and cloud capacity planning across GEICO’s hybrid technology landscape.
The Staff Engineer will partner with Infrastructure, Cloud, Hardware Procurement, Finance, and Service Provider teams to develop and scale capacity engineering solutions that support workload repatriation, quota and subscription management, forecasting, and infrastructure demand planning. This role plays a critical part in ensuring GEICO’s infrastructure is provisioned efficiently and strategically to support application onboarding, growth, and modernization efforts.
This role will help establish capacity engineering as a core function that empowers infrastructure efficiency, long-term cost predictability, and service availability across GEICO’s technical platforms. Position Responsibilities As a Staff Engineer, Capacity Engineering you will: Lead the design and implementation of systems that enable cloud and OnPrem capacity forecasting, including planning models to support application onboarding, expansion, and repatriation. Partner with application and infrastructure teams to analyze workload characteristics, optimize placement decisions, and reduce infrastructure waste through intelligent workload optimization strategies.
Develop and support internal tools and APIs that provide real-time and forecasted capacity signals to hardware procurement, infrastructure owners, and finance partners. Design and build quota and subscription management solutions to enable fair, scalable consumption of shared infrastructure resources. Collaborate with Hardware Engineering to define data-driven signals that guide purchase decisions for greenfield and brownfield environments.
Support the onboarding of service providers by developing capacity insights and demand management capabilities that align with platform growth expectations. Partner closely with Finance, Procurement, and Cloud FinOps teams to align capacity forecasts with spend and budget expectations.
Collaborate cross-functionally to maintain a strong governance model for capacity consumption, allocation, and scaling practices. Share best practices across teams and mentor engineers on platform scalability, cost efficiency, and operational resilience. Qualifications 8+ years of experience in infrastructure, platform, or capacity engineering in large-scale enterprise or hybrid cloud environments.
Demonstrated expertise in building capacity planning models, workload analysis frameworks, and forecasting pipelines for infrastructure management. Strong understanding of cloud services (e. g.
, AWS, Azure), infrastructure provisioning workflows, and OnPrem hardware life cycles. Experience working closely with procurement, hardware, or finance teams to guide infrastructure acquisition based on forecasted demand. Familiarity with workload repatriation, application migration strategies, and hybrid environment management.
Experience building internal tools and APIs for consumption by engineering or operations teams. Strong data analysis background with experience in data pipelines, dashboards, or analytics platforms for infrastructure and utilization insights. Excellent collaboration and communication skills; able to influence cross-functional stakeholders at varying levels of technical and business expertise.
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