Cloud Infrastructure and Automation Engineer

STACK Infrastructure•Plano, TX

50d•$128,260 - $146,018•Onsite

About The Position

The Cloud Infrastructure & Automation Engineer owns the cloud platform, DevOps pipelines, automation runtime environments, and operational infrastructure that power all of STACK’s AI, automation, and data initiatives. This is a hands-on leadership role—responsible for ensuring that every intelligent agent, automation workflow, RAG platform, and data pipeline moves from prototype to production rapidly, runs reliably, and scales cost-effectively. The scope spans Azure infrastructure provisioning using Terraform and Bicep, CI/CD pipeline engineering with Azure DevOps and GitHub Actions, container orchestration on AKS and Azure Container Apps, model serving and vector search infrastructure, automation runtime hosting, security hardening, and FinOps cost management. This lead also owns the deployment infrastructure for agentic and hybrid model workloads—including LLM/SLM serving endpoints, embedding compute, GPU/inference scaling, and multi-model routing. The ideal candidate is equally comfortable writing Terraform modules and reviewing architecture diagrams, with a relentless focus on deployment velocity, reliability, cost optimization, and security.

Requirements

7+ years of cloud infrastructure/DevOps experience with at least 2 years supporting AI/ML, automation, or data platform workloads at scale.
Expert-level Azure skills: Databricks, Cosmos DB, Azure Functions, Logic Apps, ADLS Gen2, Azure AI Search, Azure OpenAI Service, Container Apps/AKS, and Azure Monitor.
Strong IaC proficiency: Terraform (modules, state, workspaces), Bicep, or ARM templates with environment-templated patterns.
Hands-on CI/CD engineering: Azure DevOps, GitHub Actions, container registries, Helm charts, and blue/green/canary deployment automation.
Solid Python and Bash skills for infrastructure tooling, automation scripts, and deployment utilities.
Deep understanding of Azure networking, security (RBAC, managed identities, Key Vault, Private Endpoints, Azure Policy), and cost management.
Experience with containerization (Docker) and orchestration (AKS or Container Apps) for production workload and model serving.
Familiarity with AI platform infrastructure: Databricks provisioning, Cosmos DB scaling, AI Search management, and LLM endpoint deployment.
Must be eligible to work in the United States
Must pass comprehensive background and drug screening

Nice To Haves

Experience deploying RAG platform infrastructure, vector search clusters, and LLM/SLM serving endpoints in production.
Hands-on MLOps: model registries, experiment tracking, automated deployment pipelines, and A/B testing infrastructure.
Background in enterprise IT environments with M365, Intune, and Entra ID.
Azure certifications: AZ-104, AZ-400, AZ-305.
FinOps certification or demonstrated cloud cost optimization experience delivering measurable savings.
Experience supporting global operations across AMER, EMEA, and APAC with high-availability requirements.

Responsibilities

Design, deploy, and manage Azure infrastructure across dual EA subscriptions (Dev/Non-Prod and Production) including Databricks workspaces, AI Search clusters, Cosmos DB instances, ADLS Gen2, Azure OpenAI Service endpoints, and Azure Functions.
Implement Infrastructure-as-Code using Terraform, Bicep, or ARM templates with modular, version-controlled patterns enabling new workloads to deploy within hours.
Configure Azure networking (VNets, Private Endpoints, NSGs, Private DNS) for secure, globally distributed platform environments across AMER, EMEA, and APAC.
Build container-based deployment patterns (Azure Container Apps, AKS) for API serving, agent hosting, model inference, and automation execution.
Provision and manage LLM/SLM serving infrastructure: Azure OpenAI deployments, model endpoints, token-based scaling, and multi-region failover.
Design end-to-end CI/CD pipelines (Azure DevOps, GitHub Actions) for application deployment, model promotion, data pipeline orchestration, and automated testing with blue/green and canary patterns.
Build MLOps pipelines for model registration, versioning, A/B testing, canary deployment, and automated rollback of LLM endpoints and RAG configurations.
Deploy and manage automation runtime infrastructure: Azure Logic Apps, Power Automate, Azure Functions, Durable Functions, and event-driven triggers for intelligent workflows.
Maintain agent hosting environments (Chainlit, FastAPI, Teams bots) for the HR PM Agent and future agentic solutions, with auto-scaling and health monitoring.
Create reusable deployment accelerators (Terraform modules, Helm charts, pipeline templates) to reduce time-to-production for each successive initiative.
Drive Azure cost optimization: commitment-tier analysis, right-sizing, automated shutdown policies, and token consumption tracking across LLM endpoints.
Implement RBAC, managed identities, Key Vault integration, and least-privilege access across all platform components.
Ensure SOX compliance, data residency, and governance using Microsoft Purview, Defender XDR, and Azure Policy.
Manage secrets, certificates, API key rotation, and Entra ID integration for platform authentication across global regions.
Produce monthly infrastructure cost and performance reports with spend trends, cost-per-query, and optimization metrics.