Job title: Cloud Platform Reliability Engineer
Job Type: Full-Time
Location: Anchorage, Alaska (Hybrid)
Experience: 20+ Years
Work authorization: We are unable to provide be authorized to work in the U.S. without sponsorship.
Role Overview
We are seeking a Cloud Platform Reliability Engineer with experience more than 20 years to design, build, and engineer enterprise-scale cloud platforms supporting critical operations. This is a senior hands-on engineering role focused on software development, cloud platform engineering, distributed systems, Kubernetes, APIs, Infrastructure as Code, automation, and cloud-native architecture. The ideal candidate will have strong programming experience in Python, Go, Java, or similar languages and be comfortable building production-grade platform services rather than focusing primarily on operational support.
The engineer will develop and maintain cloud automation frameworks, Kubernetes tooling, operators/controllers, Terraform modules, CI/CD frameworks, deployment systems, internal developer platforms, APIs, event-driven workflows, and observability integrations. The role requires solving complex engineering challenges involving scalability, performance, concurrency, fault tolerance, networking, service dependencies, resource utilization, and high availability across AWS/Azure and large Kubernetes environments. Strong experience with containers, microservices, distributed systems, GitOps, and automated testing is expected.
Working closely with Cloud Engineering, Software Engineering, Cybersecurity, Data, Infrastructure, and Operations teams, the engineer will build reusable platforms that improve developer productivity and operational efficiency while maintaining strong security and resilience. The candidate should be equally comfortable writing production code, designing cloud architecture, debugging complex distributed systems, reviewing infrastructure, automating manual processes, and troubleshooting high-impact production issues.
Key Responsibilities
- Design, develop, and maintain enterprise-scale cloud platforms across AWS/Azure using modern cloud-native architecture and engineering practices.
- Write production-quality code in Python, Go, Java, or similar languages to build platform services, automation frameworks, APIs, controllers, and internal developer tooling.
- Build and maintain Kubernetes-based platforms, including clusters, operators/controllers, Helm deployments, service networking, workload scheduling, and container orchestration.
- Develop reusable Terraform/IaC modules and automation frameworks to provision, configure, secure, and manage cloud infrastructure at scale.
- Design and implement CI/CD and GitOps platforms that automate application builds, testing, deployments, infrastructure changes, and environment management.
- Engineer scalable microservices, APIs, event-driven workflows, and distributed systems with a strong focus on performance, concurrency, fault tolerance, and resiliency.
- Develop internal self-service platform capabilities that enable engineering teams to provision infrastructure, deploy applications, manage configurations, and access platform services without manual intervention.
- Build automated solutions for monitoring, observability, logging, alerting, performance analysis, and operational diagnostics across cloud and Kubernetes environments.
- Troubleshoot complex production issues involving applications, distributed systems, networking, databases, containers, cloud services, and infrastructure, and develop permanent engineering solutions.
- Design and implement high-availability, disaster-recovery, backup, failover, and resilience mechanisms for mission-critical platforms.
- Optimize cloud platforms for performance, scalability, resource utilization, and cost through capacity planning, profiling, and automated resource management.
- Integrate security controls into platform engineering workflows, including IAM, secrets management, encryption, vulnerability management, network security, and policy-as-code.
- Develop automated testing for infrastructure and platform components, including unit, integration, functional, performance, and failure testing.
Education
- Bachelor’s or Master’s degree in: Computer Science, Software Engineering, Related Engineering discipline.
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