Professional Overview
GenAI Engineer building production-ready AI systems with expertise in LLMs, agentic AI, RAG, multimodal models, and fine-tuning. Passionate about creating intelligent products across healthcare, infrastructure, and automation using Python, PyTorch, FastAPI, React, and modern AI frameworks.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built production-ready LLM applications using RAG, agentic AI, and FastAPI.
- Developed AI workflow APIs integrating PostgreSQL, validation, and automated
- Designed multimodal pipelines for retrieval, inference, and deployment-ready
- Collaborated with cross-functional teams to ship reliable AI features into p
- Improved AI response quality through evaluation, prompt optimization, and fa
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.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
