Cloud Engineer

Job Title : Cloud Engineer

Location : South Denver, CO (Onsite Interview Required)

Duration : Long Term Contract

Job Summary

We are seeking an experienced Cloud Engineer to design, implement, and manage scalable cloud infrastructures-primarily in Microsoft Azure -to support enterprise-grade applications and AI / ML model deployments. The ideal candidate will collaborate closely with engineering, product, and AI teams to build secure, highly available cloud environments, optimize performance and cost, and ensure adherence to cloud architecture standards across multiple products.

Key Responsibilities

Design, build, and maintain scalable, highly available Azure cloud infrastructures .

Support AI / ML model deployments , optimizing compute, storage, and networking for performance and cost efficiency.

Develop architecture blueprints and solution designs aligned with technology roadmaps and business goals.

Implement and enforce cloud security best practices : IAM, data protection, compliance, and monitoring.

Troubleshoot cloud infrastructure and deployment issues to ensure minimal downtime.

Collaborate with product managers, analysts, designers, and engineering teams on architecture decisions.

Contribute to the development and maintenance of cloud architecture standards across solutions.

Required Skills & Knowledge Cloud & Infrastructure

Strong knowledge of enterprise cloud solutions across private, public, and hybrid environments.

Hands-on experience with Azure (primary), plus exposure to AWS, VMware, OpenStack, etc.

Experience designing high availability , disaster recovery , and failover architectures.

Solid expertise in TCP / IP, VPN, SSL, HTTP , networking, and load balancers.

Azure & AI Engineering

Experience with Microsoft's AI / ML and data engineering ecosystem, including :

Azure ML Studio, AI Foundry

Azure Functions, Logic Apps, App Service

EventHub, Storage Account, Key Vault

AKS, Azure Container Apps / ACI

Cosmos DB, API Management

Microsoft Fabric, Purview

Virtual Networks, Private Endpoints, Managed Endpoints

Systems & Development

Strong Linux fundamentals .

Experience with database or application integration technologies.

Knowledge of open-source architectures and / or contribution history.

Strong understanding of the Data Science project lifecycle .

Experience with scalable, fault-tolerant, cloud-native systems .

Familiarity with agile / scrum practices.

Preferred Qualifications

Professional Cloud Solutions Architect (PCSA) certification.

2+ years of hands-on cloud engineering experience.