Senior Platform Engineer

What You'll Do

Delivery and Technical Work
• Build, configure, and maintain CI/CD pipelines using tools like GitHub Actions and GitLab
• Design, implement, and manage infrastructure as code using Terraform
• Build and deploy cloud-native platform environments — whether that's Kubernetes, managed container services, or other orchestration platforms depending on client environment — getting teams to a place where they can run and operate workloads in production confidently
• Implement and improve observability across client environments — metrics, logging, tracing, and alerting through tools like Prometheus, Grafana, DataDog and open standards like OTEL
• Build developer platform tooling, automation, and internal delivery infrastructure that makes engineering teams faster and less dependent on manual work
• Integrate AI tooling into DevOps workflows and delivery pipelines where it makes the most impact
• Push patterns and practices to minimize future technical debt
Coaching and Enablement
• Guide clients on DevOps best practices — and roll up your sleeves and do the work alongside them
• Train and mentor client and colleague engineers on CI/CD, IaC, containerization, and smart developer behaviors
• Help teams implement end-to-end automation of software delivery
• Lead change to remove impediments — political, financial, mental, social — for the adoption of DevOps at all levels
Liatrio Internal
• Seek and provide fast feedback — personally and for others
• Generate ideas and be willing to fail fast and demonstrate with POCs
• Drive knowledge sharing in and out of client engagements

Experience & Skills:

Engineering and Infrastructure
• You've built and maintained real CI/CD pipelines in production — designed the branching strategy, managed the toolchain, and debugged it when it breaks
• You can write and manage infrastructure as code using Terraform — you understand state management, module design, and what happens when things drift
• You've built and deployed cloud-native platform environments in a real production setting — whether that's Kubernetes, managed container services, or other orchestration platforms — and helped engineering teams get to a place where they can run and operate their workloads confidently
• You've implemented observability from scratch — metrics, logs, traces, and alerts using tools like Open Telemetry — and you understand what good looks like vs. what just produces noise
• You've worked across at least one major cloud provider — Azure, AWS, or GCP — and you know the core services, the gotchas, and how to build reliably on top of them
• You understand source control management deeply — branching strategies, merge policies, and how those decisions affect delivery speed and team collaboration
• You can review application code and empathize with the developers writing it — you can engage meaningfully in code reviews and help teams write more operable software
AI and Intelligent Systems
• You've started working AI tooling into your delivery workflows — using it to write scripts faster, debug infrastructure issues, or generate IaC — and you can speak to where it's actually helping
• You use AI coding tools as a regular part of how you work, and you're actively exploring how to apply them to DevOps and platform problems
• You have some familiarity with integrating AI capabilities into pipelines or automation

Requirements:

• 5+ years of hands-on DevOps engineering experience
• Must be authorized to work in the United States or Canada without sponsorship
• Travel availability: 25-50% depending on client needs