• Design, deploy, and continuously improve large-scale InfiniBand-connected GPU training clusters • Drive cluster-level storage performance, translating customer SLAs into internal throughput and IOPS performance targets • Build and maintain automation for cluster provisioning, OS imaging, firmware management, and day-two operations using Python • Contribute to infrastructure-as-code and CI/CD pipelines for cluster and platform management • Establish and own performance baselines across compute, network fabric, and storage layers • Identify, diagnose, and resolve performance bottlenecks across the full cluster stack • Implement and maintain observability tooling including metrics, alerting, and anomaly detection systems • Work closely with datacenter operations, cloud platform teams, ML researchers, and procurement to translate requirements into infrastructure architecture • Participate in the on-call rotation and help maintain production reliability of the training clusters

• In this role, you will be instrumental in shaping Chainlink’s developer-focused narrative in the blockchain ecosystem through clear, compelling, and technically accurate content. • As part of the Docs Team, you will create, refine, and enhance a wide range of materials that communicate Chainlink’s impact on onchain finance and asset tokenization. • Your work will span technical documentation, code deep dives, developer-focused tooling, and more. • You will collaborate closely with product managers, product engineers, developer relations, and other cross-functional teams to ensure content is both engaging and informative for global audiences. • This is a unique opportunity to contribute to one of the fastest-growing projects in the blockchain ecosystem and shape how the industry understands the future of decentralized finance.

• Leading large-scale migrations from legacy environments (ESXi 7.x) to VMware vSphere 8 across multiple geographic sites using VMware HCX for workload mobility and minimal downtime. • Designing, deploying, and maintaining VMware Cloud Foundation (VCF) environments, including the use of SDDC Manager for automated lifecycle management, patching, and upgrades of the full stack. • Architecting and managing NSX (NSX-T) infrastructures, including the configuration of Tier-0/Tier-1 gateways, load balancing, and Distributed Firewall (DFW) policies for micro-segmentation. • Extending existing PowerShell/PowerCLI and vRealize Orchestrator (vRO) workflows to automate VCF workload domain deployments and NSX object creation. • Serving as the VM Template Manager for modern operating systems, utilizing automated patching and vulnerability remediation tailored for vSphere 8 secure baseline configurations. • Managing high-performance computing clusters and MSCS VMware clustering to ensure high availability for SQL Server and other critical workloads during vMotion and site-to-site migrations. • Utilizing HCX to establish network extensions (L2) and execute live (vMotion), bulk, or cold migrations between on-premises data centers and private/hybrid cloud environments. • Creating and updating detailed design documentation (HLD/LLD), migration runbooks, and process guides to ensure compliance with federal security standards.

• Instrumentation Hands-on: Make code changes to implement distributed tracing, custom metrics and structured logs using OpenTelemetry SDKs. • Time Series Data Architecture: Design and maintain high-performance metrics pipelines using modern metrics storage solutions (time-series databases) capable of handling large volume and high cardinality. • Visualization Ecosystem: Create analytical dashboards in Grafana and advanced monitors in Datadog, focusing on the Golden Signals (Latency, Errors, Traffic and Saturation). • Multi-Cloud Operation: Configure metrics and traces collection across AWS, GCP and Azure environments, ensuring a unified view of the infrastructure. • Business Monitoring: Create time series that reflect the health of the SaaS platform and real-time betting behavior (e.g., bets/sec vs. API latency). • Error Culture: Define and implement technical SLIs/SLOs, ensuring the engineering team has actionable alerts and avoids alert fatigue.