Lead DevOps Engineer

Overview

In this role, you will shape the technical foundation for scalable AI products by owning cloud infrastructure, delivery platforms, and operational capabilities. You’ll stay hands-on across architecture, deployment, and incident response, driving reliability and developer productivity. You’ll work autonomously, make architectural decisions, and guide engineering standards across teams. This is an opportunity to influence platform strategy while delivering robust, secure systems at scale.

Pay / Benefits

• high-impact work
• technical ownership
• experienced teams
• continued development
• healthcare
• retirement planning

Responsibilities

• Define the technical direction and roadmap for cloud infrastructure and DevOps
• Architect, build, and operate secure, observable platforms across Azure, AWS, or both
• Design and improve CI/CD pipelines, infrastructure as code, and release controls
• Collaborate with software engineering and data science teams to productionize AI solutions
• Establish reusable engineering patterns for security, observability, and operational readiness
• Lead architectural decisions and evaluate trade-offs for reliability, security, and cost
• Own operational risks and incidents, derive improvements from root causes
• Utilize approved generative AI tools for automation, testing, and troubleshooting
• Provide technical guidance through design reviews, pairing, and hands-on problem-solving

Key requirements

• Significant hands-on experience in DevOps, platform engineering, or related field
• Strong expertise in Azure, AWS, or both
• Advanced experience with CI/CD, infrastructure as code, release automation, environment management
• Experience with Terraform, Bicep, CloudFormation, Ansible, or similar
• Experience with Docker and Kubernetes
• Programming/scripting skills in Python, Bash, PowerShell, Go
• Knowledge of security, IAM, secrets management, network security, vulnerability management
• Experience using generative AI tools in DevOps or engineering workflows
• Ability to work autonomously and make evidence-based architectural decisions
• Experience providing technical leadership without formal management authority
• Clear communication across engineering, data science, security, architecture, and product teams

• Clear communication
• Collaborative teamwork
• Autonomy and accountability
• Azure
• AWS
• Terraform