Professional Overview
I build AI products from zero to production. My work spans LLMs, agents, RAG, NLP, Python, React, and TypeScript, with hands-on ownership across product, backend, frontend, and deployment. I’m strongest in fast-moving environments where the problem isn’t fully defined and I’m expected to figure it out and ship!
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built clinical analytics platform for 1K+ patients and 2.7K+ assessments.
- Built NLP pipelines using BERTopic, LDA, embeddings, and topic modeling.
- Improved analytics reporting performance by 30× through caching and ETL.
- • Built real-time pose estimation using MediaPipe, WebRTC, and Canvas.
- Owned AI product features from requirements through production deployment.
Key Achievements / KPIs
- Transformed client reporting from quarterly PDFs to automated monthly dashboards
- Improved report generation performance by 30× through pipeline optimization.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built Playwright + TypeScript automation across E2E, Stage, and Production.
- Integrated parallel testing, reporting, and release validation into CI/CD.
- Built ERP, inventory, warehouse, finance, HRM, CRM, and analytics systems.
- Built ERP modules supporting 18K+ products across core business operations.
- Implemented RBAC, site management, device integrations, and analytics.
Key Achievements / KPIs
- Increased regression coverage with scalable Playwright automation.
- Delivered reusable systems across multiple enterprise projects.
Education
Field of Study: Software Engineering
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
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.
