Director, Platform Engineering

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Accelerate your career. Join the organization that's driving the world's technology and shape the future. Ingram Micro is a leading technology company for the global information technology ecosystem. With the ability to reach nearly 90% of the global population, we play a vital role in the worldwide IT sales channel, bringing products and services from technology manufacturers and cloud providers to business-to-business technology experts. Our market reach, diverse solutions and services portfolio, and digital platform Ingram Micro Xvantage™ set us apart. Learn more at www.ingrammicro.com Come join our team where you'll make technology happen in surprising ways. Let's shape tomorrow - it'll be a fun journey! Ingram Micro is seeking a Director, Platform Engineering to own both the day-to-day operational health of our technology platform and the long-term transformation of how we build, release, and run software. This is a dual-mandate leadership role: keep the lights on and evolve what those lights look like. This role sits within the Global Platform Technology organization, part of the broader CTO organization. The Director will report directly into the Executive Director, Agile Delivery & Program Management, who leads the full cross-functional technology enablement portfolio alongside Engineering. This structure ensures the role is tightly connected to both engineering execution and the broader operational and delivery agenda. The Director will lead four core disciplines; SRE, DevOps, Performance Engineering, and Release Management, with a clear, unifying transformation agenda: replace manual processes with intelligent automation, embed AI across every operational function, and build a technology operations organization that is self-sufficient, preventive, and scalable. The answer to operational complexity is not more people, it is smarter systems. Your role: THE DUAL MANDATE RUN: Day-to-Day Operations - Own the operational stability, reliability, and performance of the platform. Ensure SRE, DevOps, release, and performance functions deliver consistently against SLOs, release cadences, and quality benchmarks. TRANSFORM: AI & Automation Agenda - Lead the transformation of all four disciplines into AI-powered, self-serve functions - where automation handles the routine, AI anticipates the unexpected, and engineers focus on outcomes rather than operations. What you'll lead and transform: Site Reliability Engineering (SRE) Implement AI-powered predictive monitoring and anomaly detection to surface degradation signals before they become incidents. Build automated remediation, self-healing infrastructure, AI-triggered rollbacks, and automated runbook execution, to resolve issues without human intervention. Shift the SRE model from reactive firefighting to proactive reliability engineering, using AI insights to eliminate recurring failure patterns. Govern SLIs, SLOs, and error budgets as the framework for reliability investment, with real-time AI forecasting of compliance. Embed reliability thinking early in the engineering lifecycle - shifting reliability left, not bolting it on at the end. DevOps Design and execute an AI-driven CI/CD strategy targeting 100% touchless, end-to-end pipeline automation, zero manual intervention from commit to production. Embed AI across the pipeline for intelligent code analysis, automated testing, self-healing deployments, and anomaly detection. Architect and deliver self-serve developer platforms that empower teams to provision environments, trigger deployments, and manage releases independently. Define milestones and metrics for the automation roadmap, tracking progress toward full pipeline autonomy. Champion a culture of engineering self-sufficiency, reducing toil and enabling teams to ship faster with greater confidence. Performance Engineering Own load, stress, and scalability testing programs, ensuring the platform performs reliably under current and projected demand. Automate performance testing as a continuous activity within CI/CD pipelines, blocking releases that regress against defined baselines. Use AI to identify performance bottlenecks, forecast capacity needs, and recommend optimizations before issues surface in production. Drive FinOps practices to optimize cloud resource utilization and infrastructure spend alongside performance improvements. Release Management Own the end-to-end release process across environments, ensuring consistency, auditability, and minimal disruption to production. Automate release orchestration, approval workflows, and deployment coordination to reduce manual overhead and human error. Implement AI-assisted release risk scoring to evaluate change impact, recommend optimal deployment windows, and flag high-risk releases before they go out. Establish feedback loops between release outcomes and development practices to continuously reduce change failure rates. People and Organizational Leadership Lead a team of

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