I’m a Software Automation Engineer who turns manual, error-prone workflows into reliable, automated systems. At Infineon Technologies, I build CI/CD pipelines, enforce code quality with SonarQube, and design data pipelines that transform fragmented EDA tool output into structured, AI-ready datasets so engineers can focus on engineering, not firefighting.
Whether you need a pipeline built, a workflow automated, or an ML model deployed I ship reliable systems that work in production, not just in demos.
Real-world automation solutions that save time, reduce cost, and scale operations.
AI-powered automation for Amazon, eBay, Shopify, Etsy, TikTok Shop & WordPress. Listings, pricing, orders, inventory & customer support fully managed. 80% less manual work.
View Use Case →AI-powered marketing for UK accountancy firms: SEO automation, AI content engine, PPC optimization, email drip campaigns, social scheduling, and real-time analytics dashboard. 75% less manual effort.
View Use Case →Professional and personal projects from enterprise data pipelines to containerized ML systems.
My path from manual network operations to building CI/CD pipelines, data infrastructure, and AI agents with a concrete roadmap for Kubernetes, Terraform, LLMs, and platform leadership.
View Full Story →Three-layer AI-powered architecture: camera person detection via ML models, stateless edge gateway, and cloud processing with FastAPI, MariaDB, and real-time Chart.js dashboard. Fully containerized with Docker Compose.
View Project →Hands-on ML work including anomaly detection, time-series forecasting, and classification deployed via FastAPI endpoints and containerized services.
View Project →Pioneered Keysight Eggplant evaluation for GUI test automation. Engineered Jenkins CI/CD enhancements cutting iteration time by ~20%. Built SonarQube code quality governance reducing manual review by 15-25%. Established 17-stage EDA data pipeline with Medallion architecture for 8 tool domains.
Thesis: Automated Network Configuration Using SDN for Cloud and Edge Environments.
Implemented CI/CD practices with Jenkins and Docker, reducing release turnaround by ~30%. Automated workflows with Python, cutting manual effort by ~40%. Supported MPLS/VPN operations and reduced critical faults by ~20%.
Built troubleshooting utilities for device output parsing. Standardized support runbooks. Assisted with network automation workflows including config validation and scripted checks.
Major in Computer Science. Foundation in programming, networking, and systems engineering.
Open to discussions about automation, DevOps, AI systems, and data engineering.