• Perform system bring-up and validation, including BIOS configuration, firmware updates, and OS-level checks. • Configure and verify platform settings (BIOS, BMC, OS) to ensure systems meet performance, reliability and consistency standards. • Execute and validate firmware updates across components, including NVMe drives, NICs, and system firmware. • Identify and troubleshoot issues related to: Device initialization and visibility. • Firmware mismatches or upgrade failures. • Misconfigurations impacting performance or stability. • Understand, define, and test procedures for: Drive swaps and rebuilds. • Data integrity and system health checks. • Minimizing impact to running systems. • Monitor and validate storage device health, including basic performance characteristics and failure indicators. • Work with Linux systems to verify configuration, collect diagnostics, and assist in debugging issues. • Collaborate with senior engineers to escalate and help triage complex cross-layer issues. • Contribute to documentation and standardization of bring-up, validation, and operational procedures.

• Design, build, and operate a secure and scalable Kubernetes-based platform across cloud and/or on-prem environments • Own the full containerization lifecycle, including Docker image creation, optimization, registry management, and security best practices • Provision and manage Kubernetes clusters, ensuring high availability, scalability, and production stability • Develop, maintain, and optimize Kubernetes resources (Deployments, StatefulSets, DaemonSets, Services, Ingress, ConfigMaps, Secrets) • Design and maintain Helm charts for standardized, repeatable deployments • Implement and enforce Role-Based Access Control (RBAC) and cluster security hardening standards • Architect and maintain CI/CD pipelines for containerized workloads using modern automation and GitOps practices • Implement Infrastructure as Code (IaC) to ensure reproducible and reliable infrastructure provisioning • Monitor, troubleshoot, and optimize cluster, networking, and application performance issues • Implement observability solutions including monitoring, logging, and alerting frameworks • Drive incident response and root cause analysis for production environments • Collaborate closely with Development, QA, Security, and Operations teams to improve platform reliability and developer experience • Contribute to documentation, standards, and platform best practices

• Define and execute the enterprise AI/ML platform strategy, delivering scalable, secure, cloud-native solutions aligned to RTX’s mission and business priorities. • Lead the end-to-end architecture, integration, and production deployment of advanced AI capabilities, including generative AI, LLMs, and MLOps frameworks. • Serve as the senior technical authority, ensuring engineering excellence, governance, reliability, and compliance across platforms. • Partner cross-functionally with product, program, cybersecurity, and business leaders to drive enterprise adoption and measurable impact. • Build, mentor, and lead high-performing engineering talent while establishing best practices for CI/CD, DevSecOps, and operational sustainability.

• Design and maintain enterprise GCP landing zones aligned with governance and security standards. • Build and operate shared cloud services supporting both AI and non-AI workloads. • Implement Infrastructure as Code (Terraform) for platform, networking, and AI service enablement. • Engineer and operate GKE clusters for application and AI inference workloads. • Enable and operate approved Google AI services, including: Vertex AI, Gemini APIs, BigQuery ML. • Build secure CI/CD pipelines for cloud and AI workloads.