Cloud Engineer (Azure & AI Enablement)
Location: Hybrid (In-office Tuesday–Thursday) | South Downtown Charlotte, NC
Position Type: Full-Time, Direct-Hire
Target Compensation: $140,000 – $160,000
Work Authorization: US Citizen or Green Card Holder Required
Position Overview
Driven by private equity backing and massive organizational scale, our infrastructure team is expanding rapidly. We are seeking a high-velocity, modern
Cloud Engineer to join our Charlotte, NC hub.
We operate in a
100% Azure environment with a strong "DevOps first" mindset where
Infrastructure as Code (IaC) and automation are law. In this role, you will build out touchless, self-service infrastructure, modernize legacy tech debt, and partner directly with software and data engineering teams to host agentic AI workflows and LLM infrastructure.
If you thrive in high-autonomy settings without rigid playbooks, utilize modern AI coding assistants (GitHub Copilot, Claude Code, Cursor) to multiply your output, and move fast, this role is built for you.
What Makes This Role Exciting
- Scale & Velocity: Move fast with direct PE funding behind modernizing platforms, scaling AKS, and building touchless developer environments.
- Cutting-Edge AI Infrastructure: Active deployment of agentic AI frameworks, hosting ChatGPT/LLM integrations, and supporting Microsoft Foundry services on Azure Kubernetes Service (AKS).
- Major Initiatives: Play a core role in our multi-year Data Platform migration—connecting traditional database infrastructure into a modernized Snowflake Data Lake ecosystem on Azure.
- Modern Developer Toolkit: Enterprise access to GitHub Copilot, LLM tools, and AI coding agents to automate workflows and accelerate platform delivery.
Key Responsibilities
- Infrastructure as Code & Automation: Drive automated, touchless infrastructure deployment using Terraform (and Azure Bicep / ARM templates). Write Python and PowerShell scripts to orchestrate cloud operations.
- AKS & Modern Platform Operations: Administer and scale Azure Kubernetes Service (AKS) clusters to support application workloads, microservices, and AI/agentic bots.
- AI & Data Platform Support: Partner with Data Engineering to integrate Azure services with our Snowflake Data Lake. Build and secure infrastructure designed to host LLMs, AI agents, and automated workflows.
- Identity, Access & Security: Manage Microsoft Entra ID (Azure AD), SSO, RBAC, and API Management (APIM), embedding security guardrails directly into IaC automation modules.
- CI/CD & Developer Enablement: Support and enhance CI/CD pipelines across Azure DevOps and GitHub Actions to move the organization toward true self-service platform engineering.
- FinOps & Cost Governance: Implement tagging standards, cost-allocation monitoring, and resource optimization across our Azure footprint.
Core Requirements
QUALIFICATIONS & CRITICAL SKILLS
- Azure Expertise: Mid-level (4+ years) hands-on engineering experience in pure Azure production environments (compute, storage, networking integrations, managed services).
- Heavy IaC & Scripting Focus: Proven expertise building and managing production environments with Terraform; strong automation capabilities in PowerShell or Python.
- Kubernetes (AKS): Operational experience managing Azure Kubernetes Service (upgrades, scaling, ingress, and cluster lifecycle).
- Identity & API Management: Experience managing Microsoft Entra ID, RBAC, SSO, and Azure API Management.
- Adaptability & Drive: High-velocity problem solver who can navigate ambiguity, figure things out independently, and deliver measurable sprint goals without relying on step-by-step manuals.
- Status: Must be a US Citizen or Green Card holder.
Nice-to-Haves
- Experience leveraging modern AI tools (GitHub Copilot, Claude Code, Agentic workflows) in day-to-day engineering.
- Familiarity with Snowflake, PostgreSQL, or SQL Server data integration into Azure.
- Azure Certifications (e.g., Azure Administrator Associate, Azure Solutions Architect).
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