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Schedule Interview NowMy name is John M. and I have over 4 years of experience in the tech industry. I specialize in the following technologies: Python, Golang, DevOps Engineering, C#, F#, etc.. I hold a degree in Bachelor of Arts (BA). Some of the notable projects I’ve worked on include: Multi-Cloud Self-Service Infrastructure Platform (AWS & GCP), Retrieval-Augmented Generation (RAG) AI App on AWS, Next.js Customer Portal for Data, Reports & Subscription Management, Captive Portal Data API: Scalable User Management & Analytics Platform. I am based in Bronx County, United States. I've successfully completed 4 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
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Amazon
Developed a multi-cloud self-service platform automating GCP resource provisioning via AWS Lambda and ServiceNow at Columbia University. Researchers can request and deploy GCP projects, folders, IAM roles, and networking infrastructure seamlessly. The system leverages Terraform with Cloud Build for IaC, DynamoDB and MySQL for tracking, and Grouper for identity management. AWS SQS queues requests, ensuring secure, policy-compliant provisioning with full organizational governance.
This POC demonstrates Retrieval-Augmented Generation (RAG) using AWS Bedrock, DynamoDB, and Chroma. It delivers dynamic, context-aware responses by integrating external knowledge with LLMs. The backend uses Bedrock for embeddings and LLM processing, DynamoDB for structured data, and Chroma for vector search. The frontend, built with Next.js and TypeScript, offers a modern UI. Infrastructure is automated via AWS CDK and Pulumi, with Docker and Makefile for local development.
Developed a scalable Next.js customer management portal with real-time reporting, subscription handling, and role-based access. Key Features: - Smart loading states & background revalidation - Stripe integration for subscription billing - Clerk-based SSO & role management - Admin dashboard for reports & exports - Rate limiting & secure API access - Kubernetes deployment with CI/CD automation Outcomes: Improved operational efficiency, reduced support overhead, and enabled real-time insights for business users.
Built and deployed a cloud-native backend for an enterprise WiFi portal using GoFiber, PostgreSQL, and Redis. Key features: secure Clerk-based auth, real-time analytics, scalable job processing, and CI/CD automation. Deployed via Docker and Kubernetes. Results: reduced onboarding time by 40%, improved system reliability, and enabled seamless scaling with automated deployments.
Bachelor of Arts (BA) in Computer science and Mathematics
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