Professional Overview
AI Engineer specialized in LLM pipelines and backend systems. Built production-ready solutions at TESI reducing audio analysis from hours to under 5 minutes. Skilled in Python, LangGraph, RAG, FastAPI, and Docker. Passionate about autonomous agents and real-world AI automation.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built Python pipeline: audio transcription, summarization, and report generation
- Developed FastAPI backend with REST endpoints and role-based authentication
- Integrated OpenAI API for transcription, summarization, and keyword extraction
- Built automated test suite; system validated and deployed to production
- Designed and maintained MySQL database schema for session data management
Key Achievements / KPIs
- Reduced audio analysis from hours to under 5 minutes per session
- System approved for production after successful pilot deployment
- Automated 100% of manual audio analysis workflows
Education
Field of Study: Artificial Intelligence, Machine Learning, Big Data
Field of Study: Software Engineering, Backend Development
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.