Cloud Platform Engineer

Cloud Platform Engineer



Location: Charlotte, NC



Key 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 Platforms
• Observability (monitoring, logging, tracing)
• SRE concepts (SLOs, SLIs, reliability engineering)
• Python (automation)
• HashiCorp Vault (secrets management)

GenAI / Advanced Skills (Strong Preferred):

• GenAI Platforms / LLMs
• RAG (Retrieval Augmented Generation)
• MLOps / LLMOps pipelines

Key Responsibilities (Keywords for Search):

• Build enterprise cloud platforms (GCP + Azure)
• Implement Terraform-based reusable modules
• Design landing zones & governance frameworks
• Enable hybrid/multi-cloud connectivity
• Manage Kubernetes platforms (GKE/OCP)
• Build Internal Developer Portals (self-service infra)
• Define SLOs, reliability patterns, observability
• Support GenAI/LLM workloads and platform enablement

GCP • 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/LLMOps

Responsibilities:
• 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.