Core Technical Stack & Tooling

Technical Skills & Competencies

An in-depth breakdown of languages, frameworks, machine learning models, database systems, and infrastructure tools utilized in production.

95%

Frontend Engineering

Client Architecture & UI Systems
React Next.js TypeScript Tailwind CSS HTML5 / CSS3 JavaScript (ES6+)
92%

Backend & Distributed Systems

Microservices & REST/GraphQL APIs
Node.js Express Python FastAPI RESTful APIs GraphQL
88%

AI / ML & Large Language Models

GenAI, RAG & Agent Workflows
PyTorch OpenAI API LangChain Hugging Face Prompt Engineering Vector DBs (Pinecone)
90%

Databases & Storage Architecture

Relational, Document & Cache Layers
MongoDB PostgreSQL Redis Firebase Prisma ORM Supabase
85%

DevOps & Cloud Infrastructure

Continuous Delivery & Serverless Edge
Docker Git & GitHub Linux Server Admin CI/CD Pipelines Vercel AWS (EC2/S3)
94%

Architecture & Best Practices

Reliability, Testing & Security
System Design Postman / API Testing Agile / Scrum Performance Tuning Zero-Trust Security

How I Apply These Technologies

Principles that guide my daily architectural decisions and codebase hygiene.

Type Safety & Clean Code

I leverage TypeScript across the stack to catch structural defects early, maintaining self-documenting APIs and predictable data flow.

AI Automation Pipelines

Every AI project is built with proxy security, token streaming, automated retries, and strict schema validation for hallucination-free outputs.

Performance-First Mindset

Strict optimization of Core Web Vitals, tree-shaking, lazy-loading, database query indexing, and caching at the edge.