Bonney Lake, Washington, United States
Senior Cloud/DevOps Engineer with 9+ years building and running infrastructure for enterprise and consumer-scale platforms — including a 3.5-year engagement supporting State Farm's cloud environment, and prior work with Zillow, FedEx, DTCC, and Best Buy. I design Infrastructure as Code with Terraform and Ansible, run containerized workloads on Kubernetes and Docker across AWS, Azure, and GCP, and build CI/CD pipelines (GitLab CI, Jenkins) with SonarQube and Artifactory for quality and artifact control. My focus is reliability and security — DevSecOps practices, IAM hardening, and observability with Splunk, Datadog, and New Relic. Recent highlights: - Supported a 3-year-plus enterprise cloud environment for a Fortune 50 insurer, retained on the team through multiple cost-cutting rounds - Built multi-cloud Terraform modules spanning AWS and Azure for infrastructure provisioning at [add: number of environments/services] - Migrated legacy deployment processes to GitLab CI/CD, cutting manual release steps [add: real number] - Set up MLflow for ML experiment tracking and deployed models to production using KServe, extending DevOps practices into MLOps workflows Core skills: Terraform, Ansible, Kubernetes, Docker, AWS, Azure, GCP, GitLab CI/CD, Jenkins, Python, Linux, DevSecOps, Infrastructure as Code, SonarQube, Splunk, Datadog. Currently open to Senior Cloud/DevOps, Platform Engineering, and SRE roles at product-focused technology companies. Open to a conversation — message me directly.
- Architected and maintained multi-cloud infrastructure on AWS using Terraform, supporting production services - Automated configuration management with Puppet and Ansible across servers, reducing manual provisioning - Built log aggregation and monitoring pipelines with Splunk and Amazon Kinesis, cutting incident detection time - Wrote Python automation scripts for cost optimization, eliminating hours/week of manual work - Maintained uptime through Elastic Load Balancing configuration and proactive Linux administration - Set up MLflow for ML experiment tracking and deployed models to production using KServe, extending the team's DevOps practices into MLOps workflows
- Migrated workloads to Google Kubernetes Engine (GKE), managing containerized services across multiple clusters - Built CI/CD pipelines integrating Bitbucket, Jenkins, and Docker, streamlining the deployment process - Automated infrastructure provisioning with Terraform and Ansible across GCP environments - Implemented monitoring with New Relic, improving mean-time-to-resolution for production issues
- Built and maintained CI/CD pipelines on Azure DevOps Services, integrating SonarQube for code quality gates - Managed artifact lifecycle through Artifactory across multiple repositories - Implemented centralized logging with ELK stack and Datadog to improve operational visibility - Automated Kubernetes deployments with Terraform and Ansible on Azure
- Deployed and managed containerized applications on Pivotal Cloud Foundry alongside Kubernetes - Built GitLab CI/CD pipelines with automated SonarQube quality gates, reducing production defects - Monitored application performance with AppDynamics, improving mean-time-to-detection - Automated infrastructure provisioning with Terraform and Ansible across Azure
- Supported AWS infrastructure at consumer scale using Terraform and Elastic Load Balancing - Built GitLab CI/CD pipelines automating deployment across multiple applications - Managed Kubernetes/Docker containerized workloads, supporting frequent production deployments - Wrote Python automation and monitored via Splunk to improve incident response time