AI Platform Engineer (Network, Operations & Security)

Position Summary As an AI Platform Engineer, you will be a key technical driver in designing, operating, securing, and scaling Central AI Platform built on hybrid cloud infrastructure, Red Hat OpenShift, and RE:AI IaaS. This role bridges enterprise-grade networking, site reliability engineering (SRE), cloud platform operations, and DevSecOps. You will ensure seamless multicloud connectivity, robust security postures, high availability, and operational excellence for critical enterprise AI/ML workloads. Key Responsibilities 1. Platform Infrastructure & Operations Oversee continuous availability, performance optimization, and observability of the Azure AI and Red Hat OpenShift-powered RE:AI cloud platform environments. Manage end-to-end incident response, root cause analysis (RCA), disaster recovery (DR) strategies, and SRE practices to guarantee platform resilience. Drive platform automation through Infrastructure-as-Code (IaC) and script workflows to support model hosting, GPU workloads, and data pipeline scalability. Monitor system health, bandwidth utilization, latency, and throughput while proactively leading capacity planning and scaling initiatives. 2. Networking & Hybrid Connectivity Architecture Design, build, and maintain secure hybrid connectivity connecting RE:AI IaaS, public cloud environments (Azure/AWS/GCP), on-premises data centers, and external partner systems. Configure and manage routing protocols (BGP), network segmentation, peering, VPNs, DirectConnect/ExpressRoute, and API gateway architectures. Coordinate physical connectivity needs, including cross-connects, colocation facilities, and data center interconnects. 3. Security, Compliance & DevSecOps Enforce Zero Trust principles, firewall policies, network security zoning, encryption in transit, and privileged access controls. Oversee cybersecurity operations including vulnerability management, threat detection, endpoint detection, and SIEM integration. Ensure platform compliance with cybersecurity policies and industry standards (ISO 27001, CIS, NIST). Partner with DevSecOps and developer teams to embed security and automated observability into AI/ML lifecycle pipelines. Skills & Qualifications Bachelor’s degree in Computer Engineering, Computer Science, Network Engineering, Information Security, or a related technical discipline. Certifications (Advantageous): Networking/Cloud: CCNP/CCIE, AWS/Azure/GCP Networking or Solutions Architect Specialty Security/Operations: CISSP, CISM, or Red Hat OpenShift certifications. Required Technical Experience Experience: 5+ years of experience in cloud infrastructure administration, hybrid networking, platform engineering, or SRE environments. Cloud & Container Infrastructure: Deep expertise in Azure platform operations and hands-on experience with Red Hat OpenShift clusters, Kubernetes, or AKS environments. Networking & Security: Strong foundation in TCP/IP, BGP, SD-WAN, cloud connectivity, firewall management, and network segmentation. Automation & Observability: Proficiency in IaC (Terraform, Bicep, ARM) and scripting (Python, PowerShell, Bash), along with experience in monitoring suites (Azure Monitor, Log Analytics, Application Insights, or OpenShift observability). AI/ML Familiarity: Experience supporting or operating AI/ML infrastructure needs (e.g., GPU VMs, inference endpoints, data pipelines, model hosting). Core Competencies Systems Thinking: Strong architectural mindset capable of balancing performance, security, availability, and cost. Crisis Management: Excellent problem-solving skills and calm execution during high-pressure incidents. Collaboration: Clear communication style with the ability to bridge technical requirements across multi-disciplinary teams.