DevOps Engineer

• Own infrastructure and platform architecture, designing scalable, secure, and cost-effective AWS environments, spanning compute, containers, networking, data stores, and messaging, that support our hosted enterprise applications.
• Define and drive DevOps strategy and standards across teams: infrastructure as code practices, CI/CD pipeline architecture, deployment patterns, and environment management.
• Lead the unification and modernization of our CI/CD platform, consolidating today’s tooling (GitLab CI, Jenkins, Octopus Deploy) into a standardized, modern deployment solution adopted by engineering teams.
• Lead automation initiatives using Terraform, Ansible, and scripting (Shell, Python) to eliminate manual work, reduce configuration drift, and standardize environments.
• Drive containerization and orchestration strategy with Docker and Kubernetes, guiding adoption, cluster architecture, and operational best practices.
• Lead incident response and root-cause analysis for complex infrastructure and deployment issues, ensuring durable corrective action, improved observability, and reduced recurrence.
• Champion reliability, observability, and security, building the monitoring, alerting, and self-healing automation that catches issues before they page anyone, including SSO, IAM, and access-management solutions for hosted client environments.
• Mentor and uplevel DevOps and software engineers, raising the bar on automation, infrastructure design, debugging, and operational excellence.
• Partner with engineering leadership, development, and client-facing teams to align infrastructure roadmaps with product and business priorities, and communicate operational posture clearly to technical and non-technical stakeholders.
• Evaluate and prototype new tools and technologies, guiding adoption decisions with proofs of concept and data-driven recommendations.
• Shape our AI tooling strategy for engineering, evaluating emerging AI tools, defining standards for their use, and driving adoption across teams.
• Architect AI-augmented workflows and automation pipelines, such as autonomous agent loops that carry multi-step engineering tasks to completion, contributing to agent frameworks that optimize context and prompting across the organization.
• Mentor engineers across levels on effective AI integration into their development and operations practices, considering the broader implications of AI tooling on team productivity, code quality, and engineering culture.

Minimum Qualifications

• 7+ years of experience in DevOps, infrastructure, platform, or systems engineering roles, with demonstrated technical leadership on complex initiatives.
• Operating Systems: hands-on experience administering both Linux and Windows servers in production.
• DevOps: strong experience designing and owning CI/CD processes and tools (GitLab CI, Jenkins, Octopus Deploy).
• Containerization: strong knowledge of container technologies (Kubernetes and Docker), including production operations.
• System Automation: deep experience deploying and configuring systems with infrastructure as code (Terraform, Ansible).
• AWS: substantial experience designing and operating a broad AWS estate, including compute and containers (EC2, ECS, Lambda), networking (VPC, ALB/ELB), data stores (S3, RDS, DocumentDB, Redshift), messaging (SQS, SNS), and IAM. Exposure to AWS AI services such as Bedrock is a plus.
• Scripting: strong scripting and automation skills (Shell scripting, Python, etc.).
• Networking: solid knowledge of network protocols and concepts (TCP/IP, DNS, load balancing, etc.).
• Problem Solving: proven ability to analyze and resolve complex infrastructure and application deployment issues, and to lead root-cause investigations.
• Communication: excellent written and verbal communication, with the ability to influence engineering teams and explain infrastructure decisions and trade-offs to leadership.
• Mentorship: experience mentoring engineers and raising team capability in automation and operational practices.
  • On-Call: willingness to participate in a shared on-call rotation, with the explicit mandate that the robust pipelines and automation you build are how we shrink it over time.