Professional Overview
AI Engineer focused on turning LLM ideas into working products—building RAG pipelines, LangGraph agents, multi-agent workflows and MCP-powered tools with Python, LangChain, FastAPI and modern LLM APIs. I enjoy working with teams from prototype to deployment, debug real-world problems and learn whatever technologies are needed to ship effectively.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built and deployed a production AI Research Assistant.
- Developed PDF, DOCX and TXT ingestion with OCR and semantic chunking.
- Improved multi-hop answer accuracy by 25% using LangGraph workflows.
- Added LangSmith, RAGAS and LLM-as-a-Judge for quality monitoring.
Key Achievements / KPIs
- Improved multi-hop answer accuracy by 25%.
- Reduced retrieval latency by 10% over the baseline.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Trained a Scikit-learn model for customer support ticket routing.
- Deployed the model, reducing prediction error by 15% over baseline.
- Built an NLTK preprocessing pipeline for customer feedback analysis.
- Improved sentiment classification accuracy by 12% over raw text.
Key Achievements / KPIs
- Reduced customer support ticket prediction error by 15%.
- Improved sentiment classification accuracy by 12%.
Education
Field of Study: Bachelor of Technology in Electrical Engineering, Minor in AI
Field of Study: Bachelor of Technology in Electrical Engineering, Minor in AI
Field of Study: Bachelor of Technology in Electrical Engineering, Minor in AI
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.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
