Professional Overview
I am an AI Engineer with experience in LLM workflows, machine learning systems and dataset engineering. I build and optimize production ready RAG pipelines, data processing automation, and model evaluation environments with Python, LangChain and Docker to power scalable AI system reliability.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Developed and maintained Python-based automation and evaluation workflows.
- Lead data operations for OpenClaw, evaluating autonomous agent trajectories.
- Contributed to reproducible AI evaluation environments and debugging workflows.
- Built automated testing pipelines to validate model outputs.
- Produce high fidelity Supervised Fine-Tuning (SFT) datasets across HEART domains
Key Achievements / KPIs
- Scaled SFT dataset engineering pipelines, boosting data accuracy to 98%.
- Evaluated 1,000+ autonomous agent trajectories across sandbox interfaces.
- Built automated testing workflows, raising LLM output validation by 25%.
- Optimized backend API workflows, lowering system latency and cloud costs.
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI Business, Marketing & Strategy
Apply AI to marketing automation, content generation, customer segmentation, and revenue growth strategies.
