09/05/2026 updated
100 % available
Senior Cloud/DevOps Solutions Consultant - AWS, Azure, GCP & OTC | SRE | AI Platform Engineering
Budapest, Hungary
Worldwide
B.Sc. in Electrical & Computer EngineeringAbout me
Senior Cloud Solutions Consultant & Architect with 10+ years in IT infrastructure, DevOps/SRE, and cloud engineering, skilled in AWS, Azure, GCP & OpenStack. Expert in DevOps/SRE, Kubernetes, multi-cloud, Telco/NFV, AI infrastructure, MLOps, and AI-driven automation for enterprise cloud platforms.
AI AgentsArgo CDRAGGitHub ActionsOpenAIHelmFine-TuningLLaMAPlatform EngineeringLlamaIndexOllamaArtificial IntelligenceMicrosoft AzureCloud ComputingCloud Engineering
Welcome! I'm Muhammad Usama, your expert DevOps, Cloud, and Data Specialist/Architect. With over 9 years of experience, I'm dedicated to helping businesses achieve seamless, cost-optimized, scalable infrastructure solutions across AWS, Azure, GCP, and OTC.
I deliver end-to-end DevOps, Cloud, and Data solutions that drive innovation and efficiency. With a 100% job success track record, I've completed numerous projects, including Cloud Migrations, Automation strategies, and Infrastructure optimization initiatives.
My qualifications include:
✔️ Multi-Cloud Certified (AWS, Azure, and Oracle Cloud Certified Architect)
✔️ 3+ years as Technical Lead / Lead DevOps Engineer
✔️ Proficient in
1️⃣ Cloud Platforms: AWS, Azure, GCP, OpenStack (OTC, etc.)
2️⃣ DevOps methodologies: GitOps, Agile, CI/CD, MLOps (Machine Learning Operations)
3️⃣ Tools: Ansible, Terraform, Jenkins, GitHub Actions, GitLab, Bitbucket, FastAPI, AWS SageMaker, GCP AutoML, MLFlow, Azure for ML solutions
4️⃣ Cloud Native: Docker, Docker-Compose, Kubernetes, Helm, Kustomize, ArgoCD and Istio
5️⃣ Languages: Python, Bash and Go
6️⃣ Data Tools: Apache Kafka, Flink and Spark, SQL/NoSQL databases
7️⃣ Linux System Administration, Automation and Virtualization
Let's collaborate to transform your Cloud Infrastructure and achieve your business goals. Contact me to discuss your project requirements in private.
Looking forward to connecting with you!
Experience
Professional experience10+ years
Freelancer since2021
Languages
GermanBasic knowledgeEnglishNative speakerHungarianBasic knowledge
Project history
T Cloud Public (formerly Open Telekom Cloud (OTC)) is a European public cloud platform based on OpenStack, deployed across multiple EU regions.
• Provided DevOps/SRE, solution engineering, and operations & maintenance (O&M) support across OTC, AWS, and Azure for production cloud services
• Automated and implemented platform-wide upgrades, large-scale changes, and compute expansions on OTC using DevOps/SRE tooling and in-house O&M tools, improving scalability, security, and reliability of the platform
• Managed cross-cloud infrastructure operations on OTC, AWS, & Azure, ensuring HA, scalability, and security while optimizing costs by 20%
• Engineered scalable LLM serving infrastructure using vLLM, Llama.cpp, Qwen, and fine-tuned models, optimizing inference, security, and resource utilization for hundreds of concurrent enterprise users
• Provided DevOps, platform engineering, and L2/L3 support across AWS, OTC, and Azure — building out K8s environments, Terraform-based infrastructure automation, CI/CD pipelines, and monitoring/observability
solutions
• Supported OTC’s evolution toward large-scale AI/GPU Cloud infrastructure, spanning A100/H100s through next-gen NVIDIA Blackwell (B200/GB200/GB300s) platforms, supporting HPC, distributed AI training and inference workloads
• Helped integrate and bring online ~100 NVIDIA RTX PRO 6000 GPUs into T Cloud’s (OTC) AI Cloud portfolio, expanding GPU capacity for AI and HPC customer workloads
* Involved in Creating and Deploying CI/CD pipelines for different AI based products using tools like GitHub Actions, GitLab CI/CD etc. on AWS ECS/EKS and GCP
* Managed EKS, ECR, ECS, Docker and Docker Compose production deployments
* Deployed complete Machine Learning CI/CD pipelines using AWS and Azure DevOps for multiple projects and utilized Docker and Kubernetes for containerization and application management
* Hands on experience on developing backend code for AI products using FastAPI framework
* Implemented CI/CD pipelines and integration with model versioning tools (eg, Git, MLflow) to ensure seamless model deployment and continuous monitoring
* Developed monitoring solutions and implemented performance metrics for Computer Vision AI models in production, enabling real-time tracking of model performance
* Established standard infrastructure as code (IaC) patterns and modularized existing Terraform code for AWS / Azure Cloud Infra
* Developed and implemented end-to-end pipelines for deploying Computer Vision AI models into production environments using MLOps best practices
* Provisioned and maintained complex AWS infrastructure (EKS, EC2, RDS, IAM roles /policies , VPC, S3 buckets and Dynamodb) with advanced Terraform
* Worked with other Senior and Junior DevOps engineers to streamline and adopt the best DevOps practices
* Led daily Agile stand-up and Sprint Retro meetings for a team of over 20 members in the absence of Manager
* Utilized Jira, Shortcut, and Notion for streamlined ticket management, issue handling, and sprint planning
* Managed EKS, ECR, ECS, Docker and Docker Compose production deployments
* Deployed complete Machine Learning CI/CD pipelines using AWS and Azure DevOps for multiple projects and utilized Docker and Kubernetes for containerization and application management
* Hands on experience on developing backend code for AI products using FastAPI framework
* Implemented CI/CD pipelines and integration with model versioning tools (eg, Git, MLflow) to ensure seamless model deployment and continuous monitoring
* Developed monitoring solutions and implemented performance metrics for Computer Vision AI models in production, enabling real-time tracking of model performance
* Established standard infrastructure as code (IaC) patterns and modularized existing Terraform code for AWS / Azure Cloud Infra
* Developed and implemented end-to-end pipelines for deploying Computer Vision AI models into production environments using MLOps best practices
* Provisioned and maintained complex AWS infrastructure (EKS, EC2, RDS, IAM roles /policies , VPC, S3 buckets and Dynamodb) with advanced Terraform
* Worked with other Senior and Junior DevOps engineers to streamline and adopt the best DevOps practices
* Led daily Agile stand-up and Sprint Retro meetings for a team of over 20 members in the absence of Manager
* Utilized Jira, Shortcut, and Notion for streamlined ticket management, issue handling, and sprint planning
* Worked on various projects on DevOps, Cloud (AWS, GCP and Azure) and MLOps with global clients and diverse teams with an Agile mindset and methodologies