| Location | Austin, Texas |
Type: Remote
Coverage: Pacific Hours (8:00 AM – 5:00 PM PST and On-call every 4-5 weeks)
We are looking for a Senior/Staff Platform Engineer to build, operate, and evolve large-scale production infrastructure. This is a hands-on platform and reliability engineering role for someone who has deep experience operating Kubernetes and cloud infrastructure, troubleshooting complex production systems, and building the automation and tooling that keeps those systems reliable.
The work spans Kubernetes, Linux, cloud infrastructure, networking, observability, CI/CD, reliability, and production operations. You will write production code and automation in Go, Python, or Java, but this is not primarily a software development role. We are looking for an engineer who understands the systems underneath the applications and can independently diagnose and solve infrastructure problems across multiple layers.
This is a highly autonomous role. You will work directly with technical stakeholders, own ambiguous infrastructure initiatives from design through production, and be trusted to drive technical decisions and critical issues without requiring constant direction.
Design, build, operate, and improve production Kubernetes platforms.
Own platform-level concerns including cluster architecture, networking, workload isolation, resource management, security, upgrades, scaling, and reliability.
Troubleshoot Kubernetes beyond the application layer, including networking/CNI, scheduling, node behaviour, resource constraints, controllers, and cluster-level failures.
Operate and improve large-scale, highly available infrastructure across cloud, hybrid, virtualised, and/or bare-metal environments.
Diagnose complex issues spanning Kubernetes, containers, Linux, networking, and underlying infrastructure.
Optimise platform infrastructure for reliability, performance, scalability, and operational efficiency.
Write, maintain, and improve production tooling and automation using Go, Python, or Java.
Build software and automation that improves platform operations, reliability, deployment, troubleshooting, and developer experience.
Read, debug, and contribute to existing production codebases.
Develop internal services, APIs, integrations, and operational tooling where needed.
Automate repetitive operational processes and reduce manual intervention across the platform.
Apply sound software engineering practices, including testing, code review, maintainability, and documentation.
Own the reliability and operational health of critical production infrastructure.
Lead or contribute significantly to incident response for complex platform and infrastructure issues.
Investigate root causes and implement durable remediation rather than temporary fixes.
Define and improve SLOs, SLIs, alerting, and operational processes.
Troubleshoot systems using logs, metrics, traces, profiling tools, and system-level diagnostics.
Drive improvements in availability, performance, capacity, resilience, and operational readiness.
Contribute to disaster recovery planning, testing, and continuous improvement.
Build and maintain infrastructure as code using Terraform and related automation technologies.
Create reusable infrastructure patterns and improve automation as the platform evolves.
Build and improve CI/CD and deployment workflows supporting large-scale engineering environments.
Balance delivery speed with reliability, security, scalability, and operational requirements.
Work across infrastructure provisioning, configuration management, deployment automation, and production operations.
Participate in planning and executing production cloud or infrastructure migrations, including dependency analysis, networking, cutover, rollback, and production validation.
Build and maintain production monitoring, metrics, dashboards, alerting, logging, and distributed tracing.
Improve observability so engineers can identify and diagnose failures quickly.
Use production telemetry to identify reliability, capacity, and performance problems before they become major incidents.
Continuously improve incident detection and reduce time to diagnosis and recovery.
Work directly with customer and internal engineering teams to understand requirements, investigate problems, and drive technical solutions.
Communicate architecture, technical decisions, risks, trade-offs, and progress clearly to technical stakeholders.
Own complex infrastructure initiatives from initial problem definition through design, implementation, and production operation.
Contribute to architecture discussions, RFCs, design reviews, and technical direction.
Mentor other engineers and help improve engineering and operational practices across the team.
Operate independently in ambiguous situations and take ownership when immediate technical or management direction is unavailable.
10+ years of professional experience in Platform Engineering, Site Reliability Engineering, Infrastructure Engineering, DevOps, or related fields; 10+ years is preferred for Staff-level candidates.
Significant hands-on experience operating complex production infrastructure and distributed systems.
Demonstrated experience building and operating production Kubernetes platforms, not only deploying applications onto existing clusters.
Production programming experience with Go, Python, or Java.
Strong experience with production reliability, incident response, troubleshooting, and operational ownership.
Experience independently owning complex technical initiatives from an ambiguous starting point through production.
Experience working directly with technical stakeholders or customers and communicating complex technical topics effectively.
Degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Deep understanding of production Kubernetes infrastructure, including cluster architecture, networking/CNI, NetworkPolicy, scheduling, resource management, nodes, security/RBAC, and cluster behaviour.
Strong Linux fundamentals and hands-on production systems troubleshooting.
Strong understanding of networking concepts including DNS, routing, load balancing, connectivity, and cloud/Kubernetes networking.
Production experience with at least one major cloud platform: AWS, GCP, or Alicloud.
Infrastructure as code at scale using Terraform or equivalent tooling.
Configuration management and automation experience with technologies such as Ansible, Puppet, or similar.
Strong production debugging and root-cause analysis skills across infrastructure and distributed systems.
Observability experience using metrics, logs, traces, dashboards, and alerting platforms such as Prometheus, Grafana, OpenTelemetry, Datadog, or equivalent.
Experience with CI/CD infrastructure and modern software delivery practices.
Docker and container tooling as part of the production lifecycle.
Production coding and automation experience in Go, Python, or Java.
Understanding of high availability, capacity planning, disaster recovery, and production resilience.
Experience planning and executing production cloud or infrastructure migrations, including cutover and rollback strategies.
Experience operating large-scale or multi-cluster Kubernetes environments.
Experience with hybrid cloud, on-premises, virtualised, or bare-metal infrastructure.
Experience building or modifying Kubernetes controllers or operators.
Advanced Kubernetes networking, CNI, NetworkPolicy, service mesh, mTLS, or workload identity experience.
Multi-cloud infrastructure experience.
Experience designing and testing disaster recovery strategies.
Experience with large-scale CI/CD or developer infrastructure.
Experience with capacity planning and performance engineering.
Experience building internal platform tooling or improving developer experience.
Experience with security, infrastructure hardening, IAM, or compliance requirements.
Previous technical leadership, mentoring, or Staff/Principal-level engineering responsibilities.
Experience working directly with external customers or stakeholders in a consulting or service-delivery environment.
Exceptional written and verbal technical communication.
Strong analytical, debugging, and problem-solving ability.
High degree of ownership and ability to operate independently.
Comfortable making technical decisions and driving work forward in ambiguous environments.
Able to communicate effectively with customers, engineers, and technical leadership.
Strong technical judgment and ability to explain trade-offs rather than simply implement predefined solutions.
Able to lead technically and influence others without requiring formal people-management authority.
Comfortable working within a distributed, highly technical team.
This is a hands-on platform and reliability engineering role. We are not looking for candidates whose experience has been limited to deploying applications onto Kubernetes, consuming managed cloud services, or provisioning infrastructure without owning its production operation.
The ideal candidate has personally built, operated, troubleshot, and improved production infrastructure and can clearly explain what they owned, how the underlying systems worked, and how they approached failures and architectural trade-offs.
This role requires significant autonomy and strong technical communication. Engineers should be comfortable working directly with stakeholders and driving complex technical issues without continuous oversight.
Production coding experience is required, but it may be in Go, Python, or Java. Go is not a requirement.
Cloud migration experience is strongly preferred but is not a knockout requirement.
This role is currently open to candidates based in Brazil, Mexico, or Canada.