Manager, Full-Stack Engineering, SMAI

Job description

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities Organizational Leadership • Lead, mentor, and inspire a team of Full-Stack AI Engineers responsible for end-to-end solution delivery. • Build a culture centered around innovation, customer focus, operational excellence, engineering quality, and accountability. • Drive workforce planning, talent acquisition, onboarding, employee development, succession planning, and performance management. • Foster adoption of AI-first development practices, Agentic Coding, AI-assisted software engineering, and automation-driven productivity. • Develop future technical leaders and create growth opportunities for engineering talent across SMAI. • Establish engineering best practices, technical standards, and continuous learning programs. Full-Stack AI Solution Leadership • Lead development and deployment of AI-powered enterprise platforms supporting manufacturing, planning, quality, productivity, and operational intelligence. • Drive end-to-end ownership across:• User Experience & Front-End Engineering • Application Development & APIs • Cloud Engineering • Data Engineering & Analytics • Machine Learning • Generative AI • Computer Vision • AI Operations (AIOps/MLOps) • Platform Engineering • Partner with Product Owners, Architects, AI Scientists, and business stakeholders to define technology roadmaps and execution strategies. • Ensure successful transition of solutions from proof-of-concept to resilient enterprise-scale deployments. • Drive enterprise-wide adoption of reusable AI frameworks, engineering accelerators, and standardized development patterns. AI, Computer Vision & Generative AI Leadership • Lead engineering teams delivering:• Machine Learning Solutions • Predictive Analytics Platforms • Computer Vision Applications • Real-Time Monitoring Systems • Intelligent Automation Solutions • Generative AI Products • Autonomous Workflow Platforms • Enable enterprise AI capabilities including:• Retrieval-Augmented Generation (RAG) • Agentic AI Systems • Vector Databases • LLM Integrations • Enterprise Knowledge Platforms • Multi-Agent Solutions • Physical AI and Autonomous Systems • Drive adoption of Responsible AI principles including governance, transparency, explainability, compliance, security, and risk management. • Collaborate with AI Platform, MLOps, and Architecture teams to operationalize AI solutions at scale. Cloud Platform & Engineering Leadership • Provide technical leadership across cloud-native technologies including:• Google Cloud Platform (GCP) • Snowflake • OpenShift • Kubernetes • Enterprise Integration Platforms • Streaming Data Technologies • Drive architecture, scalability, resiliency, security, and operational excellence for enterprise cloud platforms. • Lead implementation of:• Infrastructure as Code (IaC) • DevSecOps • CI/CD Pipelines • Platform Engineering • Cloud Automation • Observability and Monitoring Platforms • Govern cloud platform utilization, cost optimization, reliability, and performance. Real-Time Analytics, Image & Video Intelligence • Lead development of advanced AI-powered solutions for:• Image Analytics • Video Intelligence • Digital Inspection • Defect Detection • Manufacturing Automation • Edge AI Applications • Architect low-latency, highly scalable systems capable of processing:• Streaming Data • Sensor Telemetry • Industrial IoT Signals • Image Workloads • High-Volume Video Streams • Drive implementation of real-time analytics frameworks supporting operational decision-making and intelligent automation. Operational Excellence & AI Operations • Ensure production systems achieve high standards for:• Availability • Reliability • Security • Scalability • Performance • Lead incident management, operational support, platform governance, and service management processes. • Establish Service Level Objectives (SLOs), operational metrics, and performance monitoring standards. • Implement automated observability, alerting, remediation, and reliability engineering practices. • Drive adoption of MLOps, AIOps, and continuous improvement methodologies. Business & Stakeholder Partnership • Collaborate closely with Manufacturing, Assembly & Test, Quality, Planning, Engineering, Operations, and Corporate Functions. • Translate business priorities into scalable technical solutions and execution plans. • Drive prioritization, resource planning, technology investments, and delivery governance. • Communicate strategy, architecture direction, technology roadmaps, and business outcomes to executive leadership. • Build strong partnerships across global engineering organizations to accelerate innovation and delivery. Qualifications & Experience Required • 10+ years of experience delivering enterpris