Jobs · Engineering · Texas

Staff Engineer, Cloud & TechOps

GameStop · Grapevine, TX · 3 wk ago
On-siteEngineeringFull-time

Key Responsibilities

  • Lead the design and optimization of GameStop’s infrastructure, leveraging your deep technical expertise to build scalable, secure, and high-performing systems.
  • Collaborate with relevant teams to ensure all systems and applications meet established performance SLAs.
  • Kubernetes Management: Lead design, optimization, and management of the various Kubernetes clusters, ensuring efficient use of resources.
  • Incident Investigation: Use deep knowledge of cloud platforms to quickly identify and resolve complex cloud incidents.
  • Independent & Collaborative Work: Operate autonomously, applying independent thought and decision-making, while also effectively leading cross-functional collaboration on complex projects.
  • Agentic AI & Infrastructure Automation: Design, implement, and maintain agentic AI systems for self-healing workflows, intelligent capacity planning, automated incident response, and infrastructure-as-code generation.

Required Qualifications

  • Technical Expertise: Strong background in IT infrastructure design, implementation, and management, with an architect-level understanding of network, storage, cloud, and server architecture.
  • Experience in Cost Optimization: Proven experience utilizing data to identify and work cross-organizationally to drive the implementation of cost-saving opportunities.
  • Project Management: Skilled in managing large-scale infrastructure projects, with a focus on performance outcomes and service level agreements.
  • Communication & Decision-Making: Excellent interpersonal and decision-making abilities, able to work independently while also fostering a collaborative environment.
  • Prior experience in retail or e-commerce infrastructure management.
  • Mastery of cloud platforms (e.g., AWS) and DevOps methodologies.
  • Agentic AI Experience: Hands-on experience with agentic AI systems for infrastructure automation (AI-driven runbook execution, LLM-based ops tooling, autonomous remediation pipelines).

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