Professional Overview
AI Engineer & Full-Stack Developer building production-grade LLM systems, AI agents, and RAG pipelines. I deliver end-to-end GenAI solutions on GCP (Vertex AI, Cloud Run) with FastAPI and React. Recently architected real-time AI governance middleware handling 100K+ requests/day at
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected real-time middleware auditing responses across multiple LLM provider
- Engineered hallucination detection and risk-content flagging mechanisms
- Built full React frontend: real-time dashboards, audit interfaces, multi-tenant
- Developed FastAPI REST APIs and streaming pipelines for low-latency interception
- Owned full product lifecycle from conception to production
Key Achievements / KPIs
- Built middleware handling 100K+ requests/day at <250ms p95 latency
- Achieved 91% precision and 87% recall in hallucination detection
- Designed multi-tenant architecture with zero cross-tenant data leakage
- Delivered live audit dashboard with <500ms refresh latency
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected AI microservices with FastAPI REST APIs for model ingestion and expo
- Developed end-to-end ML pipelines on GCP (Vertex AI, BigQuery, Cloud Run)
- Designed and deployed AI agents and GenAI solutions for workflow automation
- Built MLOps pipelines: automated retraining, monitoring, drift detection
- Orchestrated deployments with Kubernetes and Docker containerization
Key Achievements / KPIs
- Reduced processing time by 35%
- Improved classification model accuracy by 20%
- Delivered full ML cycle industrialization
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected and deployed scalable ML infrastructure on GCP
- Integrated backend APIs for prediction exposure
- Built Computer Vision models for object detection and image classification
Key Achievements / KPIs
- Optimized ML pipeline with 40% performance improvement
- Achieved 15% accuracy gain on object detection models
Education
Field of Study: Artificial Intelligence
Field of Study: Web & Mobile Applications
Field of Study: Big Data
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.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.