亚马逊Data Center Technical Support Engineering Operations Technician, AWS DCEO

THE ROLE This role will be a support engineer within the Tesla IT Infrastructure Engineering & Operations department. The Sr. Incident Response Engineer will be coordinating with cross-functional engineering teams for Incident Response & Management in terms of the high availability to Tesla Manufacturing, Business Operations, Customer Service & Experience. We help to reduce the occurrence of incidents by using efficient IT Operation monitoring, effective risk analysis and professional team collaboration. The Tesla APAC Incident Response Center is a growing team consist of professionals from diverse backgrounds, which will offer you a fantastic development environment. This role will be based on Giga Factory Shanghai, China but will provide support to Tesla Business globally considering of the growing business & great mission. RESPONSIBILITIES • Independently lead incident response and management to minimize impact and ensure optimal response times. Develop incident response plans, conduct post-mortem analyses, and organize drills to enhance preparedness. • Drive IT service management projects. Establish/optimize SOPs to reduce inter-team communication barriers, promote technical knowledge sharing, and improve team incident response capabilities. • Monitor IT infrastructure and data center operations, including servers, networks, and applications. Analyze real-time stability metrics, mitigate risks, and deliver regular operational analysis reports. • Proactively enhance team efficiency through tool automation, process refinement, and adoption of industry best practices. Support daily operations and foster a culture of continuous improvement. • Oversee infrastructure changes to minimize risks, streamline approval workflows, and ensure compliance with change management protocols.

1. Strategic Planning & Design Management - Contribute in developing comprehensive 6-8 months network implementation roadmaps aligned with AWS DC expansion targets - Create and optimize network position layouts and rack placement strategies for data centre floor space utilization - Review and contribute to High-Level Design (HLD) documentation - Coordinate with engineering teams to validate technical requirements and design specifications - Develop capacity planning models to ensure infrastructure scalability - Create standardized planning templates and methodologies for network implementations 2. Project & Resource Management - Lead end-to-end project planning for multiple concurrent network implementation initiatives - Develop and maintain detailed project schedules, milestones, and dependencies - Manage project scope, and quality parameters - Conduct risk assessments and develop mitigation strategies - Improvise and optimize planning by incorporating lessons learnt of latest deployed projects, iteratively. - Coordinate across cross-functional teams to ensure alignment on project deliverables - Track and report weekly project progress and/or otherwise informed to key stakeholders 3. Supply Chain & Inventory Planning - Develop project inventory forecasts and requirements - Optimize developed counts by utilizing prior surplus spares. - Coordinate with procurement teams for strategic resource acquisition - Manage vendor relationships and delivery schedules - Establish and stick to procurement timelines aligned with project schedules 4. Program Governance & Process Excellence - Establish and maintain project management frameworks and best practices - Develop sustainable and repeatable planning processes - Create and maintain project documentation and reporting standards - Drive continuous improvement initiatives in planning methodologies - Build and maintain stakeholder communication channels - Coordinate with regional teams for standardized planning approaches and optimized lesson learnt based iterative optimized planning.

In this role, you will be a part of the Global Business Operations team, with a particular focus on Retail Customer Care performance and decision support. Using data and quantitative techniques, the decision support team acts as a consultant to provide insights and recommendations to drive operational performance improvement at vendor and Apple contact center sites. The successful candidate will identify business problems and translate those into analytical questions, and perform thorough descriptive / predictive analysis of contact center operational metrics to advise Retail Customer Care management on operational processes and programs efficiency. The candidate should possess proven intuition for business, strong quantitative and technical background and have excellent communication skill to influence and establish relationship with wide range of cross-functional team members. RESPONSIBILITIES: Lead weekly and quarterly business reviews with collaborators and drive operational improvements by supervising primary critical metric performance across demand, staffing and quality. Perform quantitative analysis to identify trends, correlations and root causes affecting key performance indicators from achieving established goals. Based on data insights collaborate closely with site lead, area managers and vendor managers to adjust strategies and actions. Apply statistical techniques on large disparate data sources to develop automated quantitative models that will forecast quarterly critical metric targets for operational teams. Collaborate with business leaders to incorporate upcoming program change impact into the model to generate critical metric targets that align with strategic business goals, driving motivation and efficiency within operational teams. Conduct ad-hoc analyses using both structured and unstructured data and implement A/B tests to evaluate ROI and customer experience impact of staffing strategies, support case creation and evaluate efficiency of new programs. Design data models for automated reports and develop dashboards using industry standard visualization tools such as Tableau to supervise key trends of metrics and generate insights on demand, staffing and quality performance.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. As an Applied Scientist, you will - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges - Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production - Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization - Provide customer and market feedback to product and engineering teams to help define product direction