AI Engineer with 2+ years in Generative AI & Data Science
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AI/ML Engineer with hands-on experience developing enterprise AI solutions across LLMs, agentic AI, RAG/GraphRAG, computer vision, OCR/document intelligence, NLP, MLOps, and predictive analytics. Experienced in building multilingual voice-enabled assistants, document processing pipelines, knowledge retrieval systems, workflow automation platforms, and AI/ML prototypes for real business use cases. Co-author of a published smartCommit research paper and recipient of Best Research Paper and Best AI Project awards at the SLAAI International Conference. Strong foundation in AI engineering, data science, backend integration, and research-driven product development.
University of Moratuwa
BSc (Hons) in Artificial Intelligence · Artificial Intelligence
August 1, 2023 – Present
Sri Lanka Institute of Information Technology (SLIIT)
Higher National Diploma in Information Technology · Information Technology
August 1, 2022 – June 30, 2024
Holy Cross College, Gampaha
General Certificate of Advanced Level Examination · Physical Science
N/A – May 31, 2021
Wycherley International School
General Certificate in Ordinary Level Examination
N/A – May 31, 2018
KyuubiAI
AI Engineer (Part-time)
July 1, 2025 – Present
Gampaha, Western Province, Sri Lanka
Epic Lanka (Pvt) Ltd
Data Science Intern (Full-time)
April 1, 2025 – Present
Sri Jayewardenepura Kotte, Western Province, Sri Lanka
Smart Sort AI 1.0 – AI/ML Hardware Solution for Automated Waste Sorting
June 24, 2026 – Present
Manual sorting of waste is labor-intensive and not efficient. This project is an improved version of a sorting bin that automates the sorting process using AI and Machine Learning techniques by reducing the burden on sanitization workers.
View ProjectAI/ML based Commit Support System – In Collaboration with 99x
June 24, 2026 – Present
Built an AI/ML system that uses fine-tuning, dynamic RAG, Agent technology, explainable AI and next-word prediction to generate commit messages aligned with company standards by analyzing code changes, improving traceability and team collaboration. (Contribution: Standardizing the fine-tuned commit message using the dynamic RAG approach)
View ProjectMulti-Stage User Churn Prediction System – AI/ML Solution for SaaS Models
June 24, 2026 – Present
Built a churn prediction system to identify users likely to leave at different stages, helping businesses take timely retention actions. Clustering models like DBSCAN, KMeans were used to cluster the customers at different stages and the predictions were made using Ensemble models. (XGBoost and Random Forest were experimented)
View ProjectHybrid AI Itinerary Advisor - Dynamic AI Expert System with Knowledge Agent
June 24, 2026 – Present
Engineered a symbolic AI core and a dynamic knowledge agent that allows the system to do real-time research and use the expert rules engine and advise dynamic, logical travel itineraries for Sri Lanka. The system enforces hard constraints, including monsoon-based weather logic, travel time conflicts, and prerequisite checks.
View ProjectHow Transformer LLMs Work
DeepLearning.AI
June 1, 2026 – Present
Pretraining Large Language Models
DeepLearning.AI
June 1, 2026 – Present
Neo4j Fundamentals
GraphAcademy
June 1, 2026 – Present
AI/ML Engineer
SLIIT
June 1, 2026 – Present
Introduction to AI and Vector Search
MongoDB
June 1, 2026 – Present
AI Agents in LangGraph
DeepLearning.AI
June 1, 2026 – Present
smartCommit: an AI-powered Commit Message Solution
SLAAI International Conference
July 1, 2025 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit through diverse academic and professional projects, including collaborations (e.g., with 99x) and research publications. Their involvement in various AI/ML domains (Generative AI, Document & Vision AI, Data Science & MLOps) shows a broad interest and adaptability. The awards and leadership roles further indicate a proactive and achievement-oriented individual, which aligns well with a dynamic technical culture.
Soft Skills & Operational Fit
The candidate's resume highlights professional skills such as teamwork, quick learning, decision-making, communication, and handling pressure. These indicate a good operational fit for collaborative and demanding AI engineering environments. The academic and professional project descriptions suggest an ability to work on complex problems and contribute effectively to team goals.