Software Engineer | Software Development, AI & Cloud

I'm a Software Engineer with nearly two years of professional experience building software products at Brain Station 23. My experience spans software development, distributed systems, cloud technologies, and AI-powered applications.

I've worked with Go, TypeScript, Python, and modern cloud technologies, building microservices, gRPC-based systems, payment integrations, and RAG-powered applications across AWS and Azure.

Currently, I'm pursuing an Erasmus Mundus Joint Master's degree in Engineering of Data-intensive Intelligent Software Systems (EDISS) at Åbo Akademi University.

I enjoy solving engineering problems, learning new technologies, and turning ideas into practical, scalable products.

• Pursuing my Master's in Engineering of Data-intensive Intelligent Software Systems.
• Exploring agentic AI, LLM applications, and RAG architectures.
• Expanding my knowledge of machine learning, cloud computing, and distributed systems.

• Software Engineering: Backend systems, full-stack development, microservices, distributed systems.
• AI Engineering: LLM applications, RAG, AI agents, machine learning, computer vision.
• Cloud & Infrastructure: AWS, Azure, containerization, CI/CD, scalable architectures.
• Problem Solving: Algorithms, data structures, competitive programming, system design.

• 1st Runner-up — National AI Olympiad 2025 (DIU), among 160+ teams.
• Winner (one of the five teams) — Smart Unibator, SUST 2024.
• AWS Certified Solutions Architect – Associate.
• AWS Certified Cloud Practitioner.
• Solved 1,000+ programming problems across competitive programming platforms.
• Codeforces max rating: 1386 | CodeChef max rating: 1709.
• Publications in Heliyon, Artificial Intelligence in Agriculture, and ICCIT 2024 & 2025.

• ScholarDocX — A platform for managing graduate applications, documents, notes, and AI-powered assistance.
• MCP Security Gateway — An ongoing project exploring security and access control between AI agents and MCP servers.
• XLTLDisNet — Deep learning-based tomato leaf disease detection, with a deployed web application.
• XEndoSIS — Deep learning-based endoscopic image segmentation.
• DeepAQNet — Estimating PM2.5 concentrations from smartphone sky images. My B.Sc. thesis.

Languages

Frameworks & Libraries

Machine Learning

Also TensorFlow · Keras · NumPy · Pandas · Matplotlib

Databases

Cloud

Version Control

Tools

I'm always interested in interesting engineering challenges, collaborations, and opportunities to build impactful products.

Email: fahadpathan56@gmail.com

Portfolio: fahadpathan7.github.io

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