Top DevOps Jobs in Chicago, IL

The Senior Network Engineer will oversee network operations and large scale projects, providing BAU network support, mentoring helpdesk staff, and leading network migrations. Responsibilities also include collaborating on network design, supporting various systems, and implementing procedures to ensure service performance and uptime.

As an Azure Automation Engineer, you'll design, implement, and manage automation solutions using Azure services to optimize workflows. Key responsibilities include creating Infrastructure as Code templates, automating routine tasks, implementing CI/CD pipelines, and collaborating with cross-functional teams to enhance cloud operations and efficiency.

The Senior Software Engineer will develop and maintain Mezmo's Telemetry Pipeline system, collaborate with managers to understand customer needs, design supporting systems, mentor team members, and ensure high-quality code while navigating scaling challenges of large data volumes.

Provide daily tactical support for production unit, troubleshoot problems, improve process capability, analyze and resolve production issues, lead continuous improvement initiatives, manage projects, ensure compliance with safety standards, oversee capital budget, and more.

As an Early Engineer, you will engage in diverse responsibilities including greenfield feature development, managing product verticals like inventory management and accounting, and driving technology decisions while collaborating with customers and iterating on feedback.

The Principal Architect at Liatrio is a senior-level role responsible for leading technology strategy, delivering enterprise architecture solutions, and serving as a trusted advisor to clients. This position involves building client relationships, guiding technical engagement success, and mentoring team members. Extensive experience in DevOps, architectural design, and collaboration with C-suite executives is essential.

The Software Engineer will be responsible for developing large new areas within data management software, handling the entire product lifecycle, and ensuring high reliability of system software. This role demands experience with AI infrastructure at scale and solid Python knowledge. Multi-tasking and quick adaptation to new technologies are essential.