3+ years
Software engineering experience
Delivery across healthcare, automation products, AI workflows, and platform engineering.
Software Engineer + AI Engineer
I build reliable product software and AI features that can hold up outside a demo.
My work spans React and Next.js interfaces, Node.js and Python services, delivery automation, and applied AI, with experience across healthcare software, workflow products, and ML-driven applications.

Currently completing an MSc in Artificial Intelligence, focused on NLP, reliable prediction, and explainable machine learning.
3+ years
Delivery across healthcare, automation products, AI workflows, and platform engineering.
MSc in AI
Academic work focused on practical machine learning, NLP, and model reliability.
4 flagship builds
Applied AI builds and full-stack product work with clear engineering context.
Core focus
Built with React, Next.js, Node.js, Python, Docker, CI/CD, and transformer-based NLP.
I do my best work where product engineering meets delivery quality. I can move from frontend UI to backend services to CI/CD and AI integration without losing focus on maintainability.
That matters when a team needs someone who can ship across the stack, make sensible technical decisions, and keep the product stable while it is still moving quickly.
I can move from product UI to API design to delivery workflows without losing sight of maintainability.
My AI work stays practical: NLP pipelines, transformer models, explainability, and reliability-aware thinking.
I have worked on CI/CD, containerised delivery, monitoring, and production deployment instead of treating them as someone else’s job.
I care about how software behaves after release: stability, testing, observability, and real-world usability.
One project leads the story. The others show range across product engineering and applied AI.
Problem
Clinical coding work is high-volume and hard to trust when a model gives predictions without context.
What I built
A transformer-based ICD recommendation workflow with uncertainty-aware output and token-level explanations for review.
Why it matters
Pushed the project beyond raw prediction by focusing on trust, interpretability, and reviewability.
Built
A MERN and Flask product that combines market views, prediction logic, and recommendation flows in one interface.
Result
Turned a model-driven idea into a usable product flow rather than a standalone experiment.
Built
A full-stack booking application with JWT authentication and connected browse, select, and checkout flows.
Result
Showed full-stack ownership across auth, user flow design, and connected frontend-backend delivery.
Built
A transformer-based NLP pipeline for entity extraction and structured interpretation of clinical note data.
Result
Extended my healthcare AI work from classification into extraction and structured analysis.
Short version: what I built, what improved, and where I had real ownership.
CueCard AI
Built AI-assisted product workflows across frontend, backend, and automation.
Bconic
Delivered workflow tooling for marketing automation and campaign operations.
Level 33 Solutions
Modernized healthcare software across UI, services, and platform structure.
OREL IT
Focused on delivery automation and engineering workflow improvements.
Grouped by where I have actually used the tools, not by self-scored percentages.
Used in production delivery, API work, automation, and AI projects.
Used for product interfaces, workflow builders, dashboards, and responsive app shells.
Used for APIs, service integrations, workflow logic, and distributed application layers.
Used in NLP projects, transformer-based modeling, explainability work, and research builds.
Used to make releases faster, deployments more reliable, and systems easier to operate.
Supporting day-to-day engineering work across applications, automation, and testing.
My academic work strengthens my engineering profile. It is focused on AI that can be explained, evaluated carefully, and used responsibly in real systems.
2025 - 2026
Coventry University
Current postgraduate work focused on NLP, reliable machine learning, uncertainty-aware prediction, and human-centred AI evaluation.
Engineering foundation
Sri Lanka Institute of Technology, Colombo, Sri Lanka
Built my foundation in software engineering, application development, databases, systems design, and delivery-focused engineering practice.
Current MSc focus
Transformer-based NLP and explainable AI methods that keep predictions interpretable and decision-useful.
Publication
International Research Journal of Innovations in Engineering & Technology (IRJIET) · November 28, 2023
Publication on machine-learning-based recommendation for stock and cryptocurrency market analysis.
I am open to engineering roles, applied AI work, and product teams that care about quality.