Cloud & AI Infrastructure Engineer

Job not on LinkedIn

🕒 6 days ago

🇺🇸 United States – Remote

💵 $160k - $190k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷 Infrastructure Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Hanwha Energy USA

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2017

⚡ Energy

🤝 B2B

🏠 Real Estate

Energy • B2B • Real Estate

Hanwha Energy USA is the U. S. investment and incubation arm of Hanwha Energy, focused on developing long-term, sustainable energy solutions across the United States. The company invests in and operates a portfolio spanning renewable generation and battery energy storage (Hanwha Renewables), powered land and integrated energy infrastructure for hyperscale and enterprise data centers (Hanwha Data Centers), retail electricity supply to residential and commercial customers (Chariot Energy), and dispatchable generation for grid support (Hanwha Gas Power Solutions). Backed by Hanwha Group, it partners with investors, landowners, enterprise energy users, and infrastructure partners to deliver large-scale, grid-supporting projects and energy-backed infrastructure.

📋 Description

• Design and provision Azure and AI resources using infrastructure-as-code. • Establish standards for networking, identity, monitoring, security, tagging, and cloud resource governance. • Build and maintain CI/CD pipelines for AI-enabled applications, internal platforms, agents, and automations. • Implement and support logging, telemetry, monitoring, and observability for AI and cloud-based workloads. • Partner with Application Development and Data Management on secure, reliable, supportable deployments. • Manage Azure and AI platform environments across development, testing, and production. • Monitor and optimize Azure and Azure OpenAI usage and spend; right-size resources and improve cost visibility. • Partner with Finance and IT leadership on cloud cost reporting, chargeback visibility, and optimization. • Support identity, access, secrets, and security practices for enterprise cloud and AI workloads. • Define and maintain standards for backup, resiliency, recovery, alerting, and support readiness. • Troubleshoot deployment, performance, connectivity, and infrastructure issues. • Contribute to architecture discussions on hosting, integration, scaling, environment design, and operational controls. • Document cloud patterns, standards, deployment approaches, and support procedures. • Evaluate and introduce tools and patterns improving reliability, delivery speed, visibility, and cost management. • Perform other job-related duties as requested by management.

🎯 Requirements

• Bachelor’s degree in Information Systems, Computer Science, Engineering, or a related field. Equivalent experience may be considered. • 4+ years of experience in cloud engineering, platform engineering, DevOps, or infrastructure engineering. • Strong hands-on experience with Microsoft Azure services and cloud architecture. • Experience with infrastructure-as-code such as Terraform, Bicep, ARM templates, or similar tools. • Experience building and maintaining CI/CD pipelines for application and platform deployment. • Experience implementing monitoring, logging, alerting, and observability for production systems. • Understanding of identity, access control, security, and networking concepts in cloud environments. • Experience supporting production applications and cloud platforms with a focus on reliability and operational excellence. • Strong troubleshooting and problem-solving skills. • Ability to work effectively with software developers, data engineers, and technical leadership. • Preferred: Experience supporting AI or machine learning workloads in Azure. • Preferred: Familiarity with Azure OpenAI and infrastructure patterns for AI-enabled applications. • Preferred: Experience with containerization, orchestration, or modern hosting models. • Preferred: Experience with FinOps, cloud cost optimization, tagging governance, or cost reporting. • Preferred: Experience with secrets management, policy enforcement, and secure deployment patterns. • Preferred: Experience in environments with custom internal applications, integrations, and growing cloud platforms. • Preferred: Familiarity with observability and telemetry practices for distributed systems and AI applications.