Umair – AWS, Kubernetes, Terraform

A large-scale enterprise, focusing on platform engineering and infrastructure modernization. The primary objective was to abstract cloud complexity for the development team by building a custom, Python-based infrastructure framework. This framework enabled the company to move away from vendor-specific patterns toward a fully cloud-agnostic architecture, ensuring long-term flexibility and reduced technical debt.

• Architected and maintained a custom Python-based framework to extend Terraform capabilities, streamlining the management of multi-cloud resources;
• Led the modernization of legacy infrastructure workflows, replacing manual "ClickOps" with robust, version-controlled Infrastructure as Code (IaC);
• Designed cloud-agnostic deployment patterns that allowed services to run seamlessly across AWS and other major cloud providers;
• Mentored junior and mid-level DevOps engineers, conducting code reviews and establishing best practices for platform engineering;
• Automated repetitive operational tasks through advanced Python and Bash scripting, reducing manual overhead by over 40%;
• Collaborated with cross-functional development teams to provide architectural guidance on scalability, security, and performance;
• Improved the reliability of the deployment pipeline by integrating automated testing and compliance checks into the custom framework.

A high-performance cloud platform specialized in real-time 3D car visualizations and digital twins for the automotive industry. The project involved architectural modernization, moving from a legacy EC2-based CloudFormation setup to a containerized, cloud-agnostic microservices architecture. The platform supports high-fidelity rendering and complex 3D data processing at scale.

• Led the architectural transition from legacy CloudFormation/EC2 setups to a modern Kubernetes (EKS) environment;
• Scaled and managed a multi-region/multi-account infrastructure consisting of 20+ EKS clusters;
• Reduced operational costs and improved environment portability by containerizing legacy services and adopting cloud-agnostic practices;
• Developed a custom internal dashboard using Go and TypeScript to monitor real-time deployment statuses across all clusters;
• Enhanced developer productivity by implementing advanced ChatOps workflows for automated deployments and incident response;
• Strengthened platform security by integrating Trivy for automated vulnerability scanning within the CI/CD pipeline;
• Designed and maintained a comprehensive observability stack using ELK, Prometheus, and Grafana for proactive system monitoring.

A data-intensive cloud mining solution designed to process and aggregate large datasets. The project focused on a complete architectural overhaul, moving from a legacy, high-maintenance infrastructure of manual EC2 instances and self-hosted MongoDB to a fully managed, serverless-first AWS environment. The goal was to eliminate manual server management, increase data processing speed, and drastically reduce monthly AWS spend.

• Architected and executed the migration of legacy EC2-based workloads to a highly scalable AWS ECS (Fargate) environment;
• Successfully migrated a self-managed MongoDB database on EC2 to a fully managed AWS RDS instance, improving data durability and reducing maintenance;
• Decoupled and automated data processing tasks using AWS EventBridge to trigger scheduled serverless workloads;
• Achieved significant cost savings by eliminating idle EC2 capacity and implementing a "pay-as-you-go" serverless model;
• Improved system reliability and data throughput, resulting in faster data production cycles for end-users;
• Standardized the deployment process using Docker, ensuring consistent environments across development and production.

Led the IoT transformation for a premium aquarium lighting company. The challenge involved modernizing legacy hardware that lacked the original source code. By reverse-engineering hardware schematics and chip communications, we transitioned "offline" Bluetooth-enabled lights into a fully connected cloud ecosystem. This modernization allowed for global remote monitoring, complex lighting schedules, and a seamless mobile app experience for aquarium enthusiasts and professionals.

• Successfully reverse-engineered legacy hardware chips to decode bit-level communications, overcoming the lack of original software source code;
• Integrated new WiFi/IoT-enabled modules with existing hardware mainboards to enable cloud connectivity;
• Architected the cloud backbone using AWS IoT Core to manage thousands of distributed devices in real-time;
• Developed a sophisticated scheduling engine that allows users to sync aquarium light cycles with the natural habitats of specific coral species;
• Built the backend infrastructure and APIs to support a full-featured mobile application for controlling brightness, color spectrum, and automated routines;
• Collaborated closely with the hardware engineering team to interpret schematics and ensure hardware-to-cloud compatibility;
• Implemented secure, low-latency communication protocols (MQTT) between the physical devices and the AWS cloud.