Professional Overview
Python dev & AI engineer, Margaret River WA. Built 6 production AI apps: self-improving agent, agentic RAG, memory agent, AI email client, YouTube transcript analyzer, RAG doc Q&A. Stack: Python, Claude API, OpenAI, MCP, Mem0, Next.js, Vercel. IBM & Google AI certified. Open to full-time, freelance, part-time.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built 6 production AI apps using Python, OpenAI, Gemini & Claude APIs
- Engineered RAG pipelines, agentic AI systems & LLM orchestration workflowsReduce
- Reduced client content production time ~80% via prompt engineeringIntegrated Goo
Education
Field of Study: Python, Machine Learning, Generative AI, Prompt Engineering, Google Cloud AI
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
