Jiani Xing

• Built and scaled multiple AI and engineering functions across APAC and EMEA, including Gameplay AI, Game Solver, Anti-Cheat, LLM Infrastructure, Platform Engineering, and Growth • Delivered 40+ hires across senior individual contributor, management, and leadership levels, with a consistently high offer acceptance rate • Led hiring for highly specialized domains including Reinforcement Learning, Game Theory Optimization, CUDA Systems, LLM Infrastructure, Anti-Cheat Research, and AI Platform Engineering • Designed and executed talent acquisition strategies across global talent markets, building long-term pipelines spanning China, Japan, Southeast Asia, Europe, and North America • Partnered closely with executive leadership on hiring prioritization, compensation benchmarking, organizational design, and workforce planning • Developed market intelligence frameworks used to inform hiring decisions, compensation structures, and geographic expansion strategies • Mentored recruiters and helped establish scalable sourcing, assessment, and candidate engagement processes across the talent team • Drove hiring process improvements that increased recruiting efficiency, improved candidate quality, and strengthened hiring consistency across business units • Promoted from Senior AI Recruiter after demonstrating strong hiring performance and ownership across multiple critical business functions

• Led end-to-end hiring for specialized AI and engineering roles, including Reinforcement Learning, LLM Infrastructure, CUDA Systems, and Game Solver Engineering • Designed structured sourcing and evaluation workflows that significantly improved hiring efficiency and reduced time-to-hire across critical technical roles、 • Built high-quality talent pipelines across APAC and EMEA, enabling faster execution on hard-to-fill AI positions • Partnered closely with hiring managers and leadership to assess technical talent, drive candidate engagement, and improve offer acceptance outcomes

•Advised startups in Web3, AI, and emerging tech on strategic talent acquisition and market expansion. •Built remote-first recruiting frameworks to scale teams across APAC with 50% faster placement rates. •Partnered with founders to establish long-term TA roadmaps, supporting sustainable growth and retention.

Led Azure cloud infrastructure support for global enterprise environments, gaining deep expertise in distributed systems and compute platforms that underpin modern AI workloads. • Resolved complex infrastructure issues across compute, networking, and storage in production cloud environments • Partnered with engineering teams to improve platform reliability and scalability • Built strong foundation in cloud architecture, distributed systems, and large-scale compute infrastructure • Built strong technical fluency in cloud infrastructure and distributed systems, enabling effective evaluation and communication with senior AI engineers

Provided technical support for Microsoft Azure cloud infrastructure, with a primary focus on Azure Virtual Machines (VM) and cloud compute services, assisting global enterprise customers in diagnosing and resolving infrastructure-level issues. Key Responsibilities: • Troubleshot and resolved Azure Virtual Machine deployment, configuration, and runtime issues across Windows and Linux environments • Diagnosed VM provisioning failures, boot errors, connectivity issues, and performance bottlenecks using Azure Portal, system logs, and diagnostic tools • Assisted customers with VM lifecycle management, including creation, scaling, resizing, disk attachment, snapshot management, and deallocation • Investigated networking issues involving Azure Virtual Networks (VNet), Network Security Groups (NSG), IP configuration, and remote access (RDP/ SSH) • Supported storage integration scenarios, including managed disks, OS disk issues, and disk performance optimization • Guided customers in understanding Azure compute architecture, resource dependencies, and best practices for VM stability and performance • Collaborated with internal engineering teams to escalate and resolve platform- level infrastructure issues Key Technical Exposure: • Cloud Infrastructure: Microsoft Azure Compute Services • Virtualization: Azure Virtual Machines (Windows / Linux) • Networking: VNet, NSG, Public IP , Private IP , firewall rules • Remote access protocols: RDP , SSH • Storage: Managed Disks, OS Disk, Data Disk • System diagnostics and troubleshooting workflows • Cloud architecture fundamentals and distributed infrastructure concepts