Cloud Platform Engineer

Cloud Platform EngineerLocation: Charlotte, NCKey Skills:Must-Have Skills (Mandatory):GCP, Azure (multi-cloud preferred)Terraform (strong hands-on IaC)Cloud Networking & Hybrid Connectivity (VPN, VPC/VNet peering, private endpoints)Landing Zones & Cloud Governance (Org Policies, guardrails)Kubernetes (GKE), OpenShift (OCP)Platform Engineering / Internal Developer PlatformsObservability (monitoring, logging, tracing)SRE concepts (SLOs, SLIs, reliability engineering)Python (automation)HashiCorp Vault (secrets management)GenAI / Advanced Skills (Strong Preferred):GenAI Platforms / LLMsRAG (Retrieval Augmented Generation)MLOps / LLMOps pipelinesKey Responsibilities (Keywords for Search):Build enterprise cloud platforms (GCP + Azure)Implement Terraform-based reusable modulesDesign landing zones & governance frameworksEnable hybrid/multi-cloud connectivityManage Kubernetes platforms (GKE/OCP)Build Internal Developer Portals (self-service infra)Define SLOs, reliability patterns, observabilitySupport GenAI/LLM workloads and platform enablementGCP Azure Terraform Cloud Networking Landing Zones Org Policy / Governance HashiCorp Vault Hybrid Connectivity Kubernetes GKE OpenShift (OCP) Platform Engineering Observability SRE / SLOs Python Internal Developer Portals GenAI Platforms LLMs RAG MLOps/LLMOpsResponsibilities:Design, build, and operate secure, scalable GCP and OpenShift (OCP/GKE) platforms to support deployment of GenAI models, LLMs, and RAG workloads.Provision and manage cloud infrastructure using Terraform, including landing zones, networking, org policies, and hybrid connectivity across GCP and Azure.Enable MLOps/LLMOps pipelines for model deployment, monitoring, and lifecycle management, integrating Arize AI and GenAI platforms.Implement platform engineering best practices, including Kubernetes-based abstractions, internal developer portals, and self-service environments.Ensure platform security, governance, and secrets management using HashiCorp Vault, IAM, and policy-as-code.Establish observability, SLOs, and SRE practices to ensure reliability and performance of GenAI and platform services.Collaborate with data scientists, ML engineers, and application teams to onboard new LLMs, APIs, and inference services efficiently.