Professional Experience

Career Overview

Over 8 years of documented professional experience in technology leadership and cloud architecture.

Starting my technology career at 16, I've accumulated extensive experience in cloud computing, security, and software development. My journey includes positions at industry leaders like IBM and Uber, where I've led crucial technical initiatives and transformations.

DevSecOps Expertise

Kubernetes

Expert in K8s cluster management, deployment strategies, and custom operators. Implemented autoscaling solutions handling millions of requests.

Git & CI/CD

Advanced implementation of Git workflows, Github actions, Jenkins, and Cloud Build. Expertise in automated testing and deployment pipelines.

Multi-Cloud

Proficient in GCP, AWS, IBM Cloud, OCI, Azure, and Alibaba Cloud. Experience in cross-cloud architecture and optimization.

Cloud Security

Implementation of RBAC, security monitoring, and compliance frameworks across cloud platforms.

Cloud Security Engineering

  • Led critical security initiatives and vulnerability management programs
  • Implemented AWS GuardDuty and GCP Stackdriver for comprehensive monitoring
  • Developed automated vulnerability remediation systems for container images
  • Managed OS patch mitigation across large-scale infrastructure
  • Created Terraform-based security posture management

Project Ownership

Cost Management

Optimized cloud resource utilization and implemented cost-effective scaling strategies.

Product Roadmap

Created and executed technical roadmaps aligned with business requirements and goals.

Scalability

Designed systems handling millions of users per hour with high availability and performance.

Technical Expertise

Full Stack Development

Extensive experience in both frontend and backend development, with expertise in debugging complex issues.

Machine Learning

Implementation of ML/AI solutions, including SVM, feature engineering, and LLM deployments.

Data Engineering

Expertise in data pipeline development, model deployment, and DevOps for data science.