DevOps Engineer

Scentsy Inc • Meridian, ID

3d

About The Position

Scentsy is looking for a DevOps Engineer to manage development and operational activities supporting our e-commerce platform and hosted web services, including deploying and operating scalable, secure infrastructure for AI-enabled applications and automation.

Requirements

• 5+ years of DevOps Engineering experience including scripting, system deployment automation, and hardware and network infrastructure design
• Bachelor’s degree in Information Technology or demonstrated equivalent
• Solutions Expert or equivalent certification in a DevOps/Cloud/Automation area required
• Expert level troubleshooting skills
• Strong working knowledge of scripting such as PowerShell, Python, Bash, etc.
• Working knowledge of languages such as Ruby, C#, etc.
• Working knowledge of orchestration tools such as Chef, Puppet, Ansible, etc.
• Working knowledge of Cloud technologies such as Azure, AWS, etc.
• Experience with observability platforms (metrics, logs, traces) and AI-assisted monitoring or alerting
• Understanding of Infrastructure as Code patterns supporting scalable workloads
• Working knowledge of containerization and orchestration platforms (Docker, Kubernetes)
• Solid working knowledge of enterprise deployment strategies, high-availability
• Strong knowledge of Continuous Integration processes, solutions, and tools such as Jenkins, Team City, Octopus Deploy, etc.
• Advanced knowledge installing, troubleshooting, and diagnostics of Windows and/or Red Hat servers, Domain Name servers (DNS), IIS, and port security

Nice To Haves

• Experience supporting AI/ML or data-intensive production systems preferred
• Familiarity with AIOps concepts (model deployment pipelines, monitoring, automated remediation) a plus

Responsibilities

• Develop and maintain system deployment automation processes to enable teams to deploy, manage, configure, scale, and monitor their applications
• Build, configure, and manage tools for fast and reliable deployments of software
• Build tools for infrastructure monitoring and resolve any issues while running in production
• Plan, install, and test new software releases, server automation, system upgrades, and resolve software related problems for both development and production enterprise systems
• Support deployment, monitoring, and scaling of AI- and data-driven workloads in production environments
• Apply AIOps techniques to improve observability, anomaly detection, alert noise reduction, and incident response
• Collaborate with software engineers and data teams to operationalize AI/ML services with appropriate reliability, security, and cost controls

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees