About Me
Hi, I'm Zuzu
Software Engineer
Computing and Software Systems graduate from the University of Melbourne. I specialize in AI development, working with LLMs, building agentic systems, and creating robotics applications. Through Dabozai, I deliver practical AI training where students build real projects. I'm driven by turning complex technology into something people can actually use.
Education
Academic Background
Strong Academic Foundation — Combining rigorous academic training with hands-on practical experience.
Bachelor of Science (Computing and Software Systems), 2022-2025. Melbourne International Undergraduate Scholarship recipient.
Certifications
Industry-recognized credentials validating expertise
AWS Certified Generative AI Developer - Professional
Advanced skills in building and deploying production-ready AI solutions using AWS services like Amazon Bedrock.
AWS Certified AI Practitioner
Knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts and use cases.
Certified Associated Python Programming (PCAP)
Professional certification demonstrating proficiency in Python programming fundamentals and best practices.
Portfolio
Projects
Key projects showcasing practical application of AI and software development skills.
Built LLM-backed mental health services navigation chatbot with RAG implementation, vector search, and geofencing for Victoria. Tech stack: Python, LangChain, Supabase (Postgres + pgvector), React, FastAPI, Google Cloud Run.
Working as part of the IT operations team, automated day-to-day operational tasks including data loading and cleaning for CMDB service team, identifying unused AWS resources, generating billing reports per department, full inventory across accounts/regions, identifying stale IAM users, checking publicly accessible S3 buckets, and generating IAM access reports.
Built an AI-powered solver for the Sokoban box-pushing puzzle game. Implemented Dijkstra's graph search algorithm with custom priority queue and hash table for efficient state-space exploration. Developed deadlock detection optimizations to prune unsolvable states early. Tech stack: Python with custom data structures.
Worked in a team to investigate the relationship between Netflix content descriptions and their associated ratings across genres. Built genre prediction model using Logistic Regression on TF-IDF vectorized descriptions. Developed Random Forest regression model to predict IMDB/TMDB scores. Performed data preprocessing including lemmatization, stop word removal across ~5,850 titles. Tech stack: Python, scikit-learn, NLTK, spaCy, matplotlib, pandas.
Expertise
Technical Skills
Technologies and frameworks I work with
LangChain, Strands Agents, AWS AgentCore, AnythingLLM, LangFlow, Composio, Claude Code, Prompt Engineering, RAG Systems, Transformers Architecture
Python, React, TypeScript/JavaScript, FastAPI, Supabase (Postgres + pgvector)
AWS (Lambda, API Gateway, SageMaker), Google Cloud Platform (Cloud Run), Docker, Vercel
Computer Vision, Robotics, Sensors (temperature, humidity, motion), Object Recognition
Agile/Scrum methodology, Sprint planning, Stakeholder management, POC evaluation
PostgreSQL, Supabase, pgvector, Vector databases, Data preprocessing, ETL pipelines, Pandas, Data cleaning and transformation
My Values
Principles that guide my work
Quality & Innovation
Building reliable software with emerging technologies, always seeking companies that value quality and continuous improvement.
Ownership & Quick Learning
Taking full ownership of tasks and rapidly learning new tools and technologies to deliver results.
Knowledge Sharing & Training
Through Dabozai, providing structured Gen AI and robotics training with hands-on labs, helping others build practical skills.
Collaborative Teamwork
Working effectively in teams, staying calm under pressure, and supporting colleagues to achieve shared goals.
Contact
Get in Touch
Melbourne, Australia
linkedin.com/in/zulaikhahabib