11/11/2026 updated
100 % available
DevOps Engineer | Cloud & AI Infrastructure
Dallas, USA
Only remote
Bachelor's Degree in Computer ScienceAbout me
DevOps Engineer with 6+ years of experience in GCP and Azure, specializing in CI/CD, Terraform, Kubernetes (GKE/AKS), cloud infrastructure, and AI/LLM systems. Focused on automation, reliability, performance, monitoring, and cost optimization.
Amazon Elastic Compute CloudMicrosoft AzureDevOpsScrum MethodologyElastic LogstashAzure Machine LearningVMware InfrastructureGoogle CloudCloud Platform SystemInfrastructure as Code (IaC)BackendGitLabGitGitlab-ciKubernetes
Cloud Platforms & Infrastructure
Extensive experience with Google Cloud Platform (GCP) including GKE, Cloud Run, Pub/Sub, Cloud Functions, and Cloud Storage, as well as Microsoft Azure including AKS, Azure DevOps, Azure Functions, Data Factory, and Blob Storage. Design and automation of cloud-native infrastructure across multi-cloud environments.
CI/CD & DevOps Engineering
Building and optimizing CI/CD pipelines using GitHub Actions, GitLab CI, Azure DevOps, and Jenkins. Infrastructure as Code with Terraform and Helm, enabling streamlined development processes and reducing deployment time significantly.
Containerization & Orchestration
Management of Kubernetes clusters (GKE, AKS, EKS) in production environments, achieving high system uptime. Containerization using Docker and orchestration of distributed workloads including AI/ML model deployments.
Monitoring & Observability
Setup and maintenance of monitoring systems using Prometheus and Grafana as well as Cloud Monitoring. Log aggregation and analysis with the ELK Stack (Elasticsearch, Logstash, Kibana), improving system alert response times and incident management.
Programming & Scripting
Primary programming language Python for automation and tooling, complemented by Bash scripting for server provisioning, environment configuration, and deployment pipeline automation.
AI/ML Infrastructure Support
Support of AI/ML and LLM models in production, ensuring infrastructure meets high-performance and low-latency requirements. Background in data pipelines and backend services with a focus on reliability and performance optimization.
Version Control & Collaboration
Version control using Git with GitHub and GitLab. Agile and Scrum collaboration methodologies applied across distributed and hybrid team environments.
Cloud Cost Optimization
Introduction and application of cost management tools and strategies, achieving significant reductions in cloud infrastructure costs while maintaining performance and reliability.
Experience
Professional experience0 - 5 years
Freelancer since2025
Languages
EnglishNative speaker
Project history
Architected and automated cloud infrastructure on GCP and Azure, reducing deployment time by 40%. Built and optimized CI/CD pipelines using GitHub Actions and Terraform. Managed Kubernetes (GKE/AKS) clusters, improving system uptime to 99.97%. Supported AI/ML models in production ensuring high-performance and low-latency requirements. Introduced cost management tools, cutting cloud infrastructure costs by 25%.
Implemented Infrastructure as Code using Terraform for multi-cloud environments (AWS and Azure). Led the migration of legacy infrastructure to Kubernetes (EKS/AKS), reducing deployment failures by 30%. Automated server provisioning, environment configurations, and deployment pipelines, reducing manual errors by 60%. Supported backend services and data pipelines, improving processing speeds by 40%. Set up and maintained monitoring systems (Prometheus, Grafana), improving system alert response times by 50%.
Designed and managed cloud infrastructure for applications running on AWS and Google Cloud Platform. Optimized the CI/CD pipeline for faster deployment cycles, decreasing average deployment time by 35%. Automated infrastructure scaling policies, improving system availability during peak loads by 20%. Implemented log aggregation and alerting systems for production environments, cutting incident response times by 25%.