AI-Driven DevOps Engineer for Automation & Reliability

Allegis Group

Hanover (MD)

On-site

USD 96,000 - 145,000

Full time

20 hours ago

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Benefits offered by this job

Medical, dental & vision

401(k) Retirement Plan

Time Off/Leave (PTO, Allegis Group)

Job summary

Allegis Group in Hanover, MD seeks a DevOps Engineer to advance automation, observability, and AI-enabled capabilities across enterprise platforms.

You will partner with engineering, release, and production support teams to implement scalable solutions, improve incident response, and boost platform reliability. This hands-on role emphasizes modern operational engineering practices and scalable automation.

Qualifications

Bachelor's degree in computer science, information systems, engineering, or equivalent combination of education and work experience.
6+ years of experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, Operational Engineering, Automation Engineering, or enterprise operational support environments.
Experience working across enterprise technology platforms such as Google Cloud Platform (GCP), GitHub, Salesforce, or comparable cloud, source control, and business application platforms.
Strong understanding of enterprise operational workflows, operational support models, and platform reliability practices.
Experience with CI/CD pipelines, release orchestration, environment management, and DevOps operational processes.

Responsibilities

Design, develop, and maintain intelligent operational solutions, automation workflows, scripts, integrations, and orchestration capabilities across DevOps, Release Management, Test Automation, and operational ecosystems.
Identify operational bottlenecks, repetitive support activities, and manual engineering processes suitable for automation and operational optimization.
Independently drive operational improvement initiatives from discovery through implementation, partnering with peer teams, senior DevOps engineers, and cross-functional stakeholders to deliver measurable process and automation outcomes.
Implement AI-enabled operational capabilities focused on incident visibility, monitoring, alert correlation, workflow automation, operational analytics, engineering efficiency, and AI-assisted development practices using tools such as GitHub Copilot, Claude, or similar platforms.
Improve observability and operational visibility through dashboards, monitoring integrations, alerting, logging, analytics, reporting, and release insight solutions across enterprise platforms.