I build AI agents and retrieval augmented generation systems that go from prototype to production. I'm an AI Developer Intern at ExpertEase AI in Adelaide and a Master of Data Science (Artificial Intelligence) student at Flinders University.
I'm an AI engineer based in Adelaide who enjoys taking an idea all the way to something people can actually use. For the past two years I have designed and delivered generative AI applications for clients as a freelance AI engineer: RAG chatbots, autonomous agent systems and automation tools built with Python, LangChain, LangGraph and FastAPI, and deployed with Docker, Kubernetes, Microsoft Azure and Google Cloud.
Today I'm an AI Developer Intern at ExpertEase AI in Adelaide, working on AI agent development, while completing a Master of Data Science with an Artificial Intelligence specialisation at Flinders University, where I hold the Go Beyond Excellence Scholarship.
Earlier I worked as an Associate Engineer at L&T Technology Services on Azure cloud applications and SQL Server data layers, and completed a machine learning internship with E Cell IIT Hyderabad. I'm also a published researcher, with a book chapter on real time traffic surveillance using deep learning.
I care about clean engineering, honest evaluation of models and agents, and building things that save people real time.
From enterprise cloud engineering to shipping AI agents for clients.
Australian workplace experience: Store Team Member at Woolworths in Adelaide (until September 2026), where I built strong customer service, teamwork and reliability in a fast paced environment.
Open source projects that show how I design, build and deploy AI systems.
A visa aware job search assistant. A LangGraph pipeline searches SEEK, reads each full job ad, checks it against the user's visa (500, 485, 482 or PR), ranks jobs on visa fit and resume skill match, and generates tailored resumes and cover letters with Groq hosted LLMs.
An autonomous project building agent. Give it a project idea and tech stack, and a LangGraph workflow plans the work, generates a runnable starter application with README and setup steps, packages it as a zip and can push it straight to GitHub.
Ask questions about any YouTube video in plain English. A four stage RAG pipeline extracts video metadata, loads the transcript, indexes it in FAISS with Google Gemini embeddings and generates context aware answers.
A minimal, working Agent to Agent (A2A) workflow built with the official A2A Python SDK. A Greeting Agent server publishes its Agent Card, and a client discovers the agent and sends it messages over the protocol.
Deep learning system for real time vehicle detection, classification and congestion analysis from traffic video, designed for scalable smart traffic management. This work became a published book chapter with Cambridge Scholars Publishing.
Coursework includes artificial intelligence, statistical learning, probability, natural language processing and cloud computing.
★ Go Beyond Excellence ScholarshipGraduated with a CGPA of 9.13 out of 10.
★ CGPA 9.13 / 10Real time deep learning vehicle detection, classification and congestion analysis using YOLOv3, OpenCV and Python for scalable smart traffic management.
Presented research on computer vision and intelligent automation systems to an interdisciplinary engineering audience.
Connected with the Microsoft Adelaide community and a regular at local tech events and meetups, where I learn from and share with other builders.
I follow AI research closely, especially agents, retrieval and model evaluation, and turn what I learn into small open source projects.
Chess for strategy and patience, and sports for energy and teamwork.
I'm open to AI, machine learning and data roles in Adelaide or remote across Australia, including internships, graduate programs, casual, part time and contract work. The fastest way to reach me is email or LinkedIn.