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Schedule Interview NowMy name is Mathew S. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: React, JavaScript, node.js, vue.js, DevOps, etc.. Some of the notable projects I’ve worked on include: LLM Chat Interface – Natural-Language Access to Identity Data, Model Context Protocol (MCP) Server, IAM Insights DataViz Chart, Audetic, GoDeploy. I am based in Satellite Beach, United States. I've successfully completed 5 projects while developing at Softaims.
I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.
Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.
I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.
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Amazon
Enable natural-language querying of AKA Identity data through an LLM-powered chat interface embedded in FOH. Users can ask questions like ‘Show me employees who have been recently terminated who still have access’ and receive structured, expert analysis with actionable insights.
Enable AI systems to query and analyze identity-management data through standardized protocols, allowing integration with tools like Claude Desktop and other MCP-compatible clients.
The Rainbow Chart translates dense security-insight aggregates into an at-a-glance radial risk map. Raw API data flows through a memoized transformer, into a responsive layout engine, and finally renders as layered SVG pies with accessible color palettes. A transparent interaction layer plus stateful tooltip hooks deliver smooth, informative UX while keeping the visual footprint clean. The modular architecture (data, state, layout, rendering, interaction) makes the component easy to extend, for example, adding keyboard navigation or new data dimensions, without touching core logic.
Audetic transforms everyday environments by applying real‑time intelligent audio filtering powered by deep learning. It separates speech from noise to deliver personalized soundscapes that enhance clarity and focus—ideal for hearing aid users navigating noisy public spaces. The production system runs on efficient on-device deep neural networks and cloud‑based microservices, ensuring fast processing. The team leverages novel ML algorithms optimized for mobile and edge deployment, combining computational neuroscience techniques with AI to deliver seamless, noise‑adaptive audio experiences .
GoDeploy is a platform that simplifies the deployment of web applications by packaging them into production-ready containers. It enables developers to host multiple single-page applications under one domain, manage custom domains, enable HTTPS, and roll back deployments with ease. The open-source CLI tool allows for local previews, container builds, and seamless deployment to self-hosted or cloud environments. Designed for speed and simplicity, GoDeploy supports scalable, multi-tenant web app delivery with minimal configuration.