Professional Overview
AI Engineer with 1.5 years of experience specializing in LLMs, RAG, Agentic AI, LLM evaluation (LLM-as-Judge), NLP, and MLOps. I have developed production-ready systems and authored a survey on LLM-as-Judge. Passionate about both research and building scalable AI solutions that deliver real impact.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Designed and developed LLM evaluation systems including LLM-as-Judge frameworks
- Built Agentic AI database assistants for intelligent data querying and interacti
- Developed an enterprise document assistant integrated with real regulations and
- Implemented and optimized RAG pipelines for production-ready AI systems
Key Achievements / KPIs
- Improved system accuracy by ~30% through continuous benchmarking and refinement
- Increased system deployment capacity while reducing API costs by 50%
- Successfully delivered production-ready Agentic AI and evaluation systems
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Designed and developed LLM evaluation systems including LLM-as-Judge frameworks
- Built Agentic AI database assistants for intelligent data querying and interacti
- Developed an enterprise document assistant integrated with real regulations and
- Implemented and optimized RAG pipelines for production-ready AI systems
Key Achievements / KPIs
- Improved system accuracy by ~30% through continuous benchmarking and refinement
- Increased system deployment capacity while reducing API costs by 50%
- Successfully delivered production-ready Agentic AI and evaluation systems
Education
Field of Study: Machin learning and generative models
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
