Available for opportunities
Philip Niron
Nithianandan
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Software Engineer with 4 years of industry experience building scalable applications across enterprise, cloud, and full-stack environments.
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Software Engineer with 4 years of industry experience building scalable applications across enterprise, cloud, and full-stack environments.
I'm a Software Engineer with 4 years of industry experience delivering production-grade software across enterprise, cloud, and full-stack environments. My work has spanned sectors including aviation and telecommunications, where I've contributed to complex, client-facing systems that serve real users at scale.
I bring strong backend development capability alongside practical full-stack experience, with a particular interest in designing systems that are both technically sound and impactful. Whether building microservices, integrating third-party platforms, or crafting intuitive interfaces, I focus on quality, maintainability, and performance.
I'm driven by the challenge of turning complex requirements into elegant, high-impact solutions — and I'm always looking for the next meaningful problem to solve.
{
"name": "Philip Niron Nithianandan",
"role": "Software Engineer",
"experience": "4 years",
"stack": {
"backend": [
"Java", "Spring Boot",
"Python", "Flask"
],
"frontend": ["React", "JavaScript"],
"cloud": ["AWS"]
},
"domains": [
"Aerospace & Defence", "Telephony",
"Healthcare AI"
],
"publication": "IEEE MIPR 2026",
"available": true
}Technologies I've worked with across enterprise and personal projects.
A selection of enterprise deliveries and personal builds.
An AI-assisted radiology report generation system that transforms chest X-ray images into structured diagnostic reports. Built on a five-stage local pipeline: preprocessing, OCR, BEiT vision encoding, Claude Sonnet via Amazon Bedrock, and Pydantic validation. RadLens addresses a critical bottleneck in clinical radiology workflows. Trained on the IU X-Ray dataset (3,307 frontal images). Accepted for presentation at the IEEE MIPR 2026 Health-MM Workshop, Bangkok.
An AI-powered medical analysis application designed to bring intelligent diagnostic support to patients and healthcare professionals. Leverages RAG architecture with Gemini LLM to surface actionable insights from medical data.
Aviation maintenance software engineered to guarantee the availability of airworthy assets, maintain operational quality, reduce the environmental impact of maintenance activities, and provide tools to meet long-term performance goals.
Developed omnichannel Intelligent Virtual Assistants to engage customers across diverse businesses and domains, integrating voice and digital channels for seamless automated interaction.
A CNN-based Android application developed to detect Fall Army Worm attacks in corn leaves. The app uses image classification powered by a convolutional neural network to help farmers identify crop threats early and take preventive action.
4 years of professional software engineering across enterprise product companies.
Academic foundations underpinning my engineering practice.
I'm open to new software engineering opportunities. Whether you have a role in mind, a project to discuss, or just want to connect — feel free to reach out.
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