Professional Overview
AI Engineer (GenAI) with 16+ months of hands-on experience building production-grade Agentic RAG systems, LLM-powered applications, and enterprise AI platforms. Delivered a full-stack Skill Intelligence Platform using Google Gemma-3 with multi-agent orchestration, semantic retrieval pipelines, weighted skill-matching algorithms, and real-time data.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Architected and deployed a production-grade Agentic RAG system using Google Gemm
- Designed an LLM prompt engineering pipeline to extract Skill Name, Min/Max Exper
- Built multi-agent orchestration workflows using LangChain/LangGraph with semanti
Key Achievements / KPIs
- 70% reduction in manual skill-tagging effort via LLM-powered JD parsing in prod.
- 200ms P95 API latency across concurrent enterprise workloads on a 500+ employee
Education
Field of Study: Computer science
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.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
