Help & Supportcareers@gravityer.com
AI Engineer with 1+ years in Artificial Intelligence & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven final-year IT undergraduate at the University of Moratuwa, specializing in Artificial Intelligence and Machine Learning, with hands-on industry experience in developing AI-powered applications and intelligent systems. Skilled in machine learning, deep learning, data-driven problem solving, and scalable software development.
University of Moratuwa
BSc (Hons) · Information Technology
June 1, 2022 – June 1, 2026
Sivali Central College
Physical Science Stream
March 1, 2018 – October 1, 2020
NovaCodex
Associate Software Engineer (Part-time)
November 1, 2025 – May 1, 2026
Moratuwa, Western Province, Sri Lanka
Creative Software
Intern Software Engineer (R&D)
March 1, 2025 – September 1, 2025
Colombo, Western Province, Sri Lanka
Multi-Agent A2A System
March 1, 2026 – Present
Designed and implemented an autonomous Agent-to-Agent (A2A) communication system enabling multiple AI agents to collaborate and exchange contextual information dynamically. Developed modular Host and Remote agent architectures supporting intelligent task delegation, workflow orchestration, and feedback-driven coordination. Implemented multi-agent communication pipelines and reasoning workflows using CrewAI, LangGraph, and Google ADK frameworks. Built proof-of-concept demonstrations showcasing cross-agent collaboration, contextual decision-making, and autonomous task execution. Tech Stack: Python, CrewAI, LangGraph, Google ADK, FastAPI, LangChain
Ontology-guided GNN for Semantic Candidate Matching
March 1, 2026 – July 1, 2026
Designed a software industry ontology and knowledge graph schema to model fine-grained skills and semantic relations. Constructed a heterogeneous KG (Job, Candidate, Skill nodes) in Neo4j/RDF and implemented automated skill extraction and mapping from job descriptions and CVs. Implemented an interpretable rule-based Fit Score to compute job-candidate compatibility using ontology relations and generate human-readable explanations. Built a GNN over the ontology-guided KG to learn Job and Candidate embeddings and compute embedding similarity. Combined ontology-based scoring and GNN similarity to produce matched candidates Tech Stack: Python, Neo4j/RDF,PyTorch, PyTorch-Geometric, spaCy, pandas, scikit-learn
Domain-Adapted Farming LLM
June 1, 2025 – September 1, 2025
Developed a domain-adapted GPT-2 based language model for Sri Lankan tea cultivation using a two-stage fine-tuning pipeline with PEFT techniques. Performed domain adaptation on agricultural literature using LoRA (Low-Rank Adaptation) to improve tea farming knowledge representation. Implemented supervised fine-tuning (SFT) on question-answer datasets to generate context-aware and task-specific agricultural responses. Optimized model training and deployment using 4-bit quantization, adapter merging, and progressive fine-tuning for improved memory efficiency and inference performance. Built an intelligent assistant capable of providing recommendations on planting methods, pest diagnosis, and fertilizer planning for tea farming. Tech Stack: Python, PyTorch, Transformers, Hugging Face, LoRA, Pandas
Developer productivity analytical system
March 1, 2025 – September 1, 2025
Implemented developer productivity analytics using DORA and SPACE metrics to track team performance. Developed interactive analytics dashboards using React and TypeScript for real-time insights. Integrated secure data collection and multi-platform connectivity with GitHub and Azure DevOps APIs using Python. Implemented CI/CD pipelines with Azure DevOps and deployments on on-premise Apache Tomcat environments. Tech Stack: Python, .Net core, React, TypeScript, Entity Core, MSSQL, Azure, PyQt6
Tea Farming Support Assistant
May 1, 2024 – July 1, 2024
Developed a modular agent architecture with a central FastAPI service that classifies user queries using an LLM and routes them to specialized services. Disease Service using retrieval-augmented generation (RAG) with Pinecone vector database and web search Fertilize Service providing personalized recommendations using weather APIs, tea land data, historical records Designed a Help Service for company policy and FAQ retrieval leveraging Pinecone vector database. Integrated LangChain and LangGraph for agent orchestration and developed the frontend using Next.js. Tech Stack:Python, FastAPI, Next.js, LangChain, LangGraph, Pinecone, Scikit-learn, Pandas, DuckDuckGo
Gen AI with Transformers
Unknown
June 19, 2026 – Present
Azure Fundamentals (AZ - 900)
Unknown
June 19, 2026 – Present
AI Agents Using RAG
Unknown
June 19, 2026 – Present
Cultural Fit Analysis
The candidate's academic background from a reputable university (University of Moratuwa) and participation in multiple academic projects, including those with a social impact (Tea Farming Support Assistant, Domain-Adapted Farming LLM), indicate a proactive and engaged individual. The diversity of projects, ranging from theoretical (Ontology-guided GNN) to practical applications (Multi-Agent A2A System), suggests adaptability and a broad interest in AI. Their internship experience at 'Creative Software' and part-time role at 'NovaCodex' show exposure to professional environments, which is positive for cultural integration. The candidate's focus on AI/ML aligns well with an AI Engineer role, demonstrating a clear career interest.
Soft Skills & Operational Fit
The candidate's resume highlights problem-solving, critical thinking, teamwork, and agile practices, which are crucial for operational fit in a senior engineering role. Their academic and project work demonstrates an ability to tackle complex problems and collaborate effectively. The experience in developing a 'Developer productivity analytical system' also suggests an understanding of operational efficiency and performance tracking.