Praise Jaravani

Software Engineer & Cyber Security Consultant

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Hey there! I'm Praise

Building digital solutions that power the future

Software engineer and associate cyber security consultant at MWR CyberSec, with three years of engineering across .NET, React and Python, plus machine learning and blockchain work.

My Toolkit

Technical Skills

Frontend

  • React
  • Next.js
  • Angular
  • Blazor
  • TypeScript
  • JavaScript
  • HTML/CSS
  • TailwindCSS

Backend

  • Python
  • Node.js
  • .NET Core
  • FastAPI
  • Django
  • Flask
  • GraphQL
  • Java
  • C/C++
  • C#

Security

  • Penetration Testing
  • Burp Suite
  • Nmap
  • Gobuster
  • Nikto
  • Hashcat

AI & ML

  • Machine Learning
  • Hugging Face
  • Llama
  • RAG
  • pgvector
  • NLP
  • TensorFlow
  • Data Analysis

Blockchain

  • Algorand
  • Smart Contracts
  • TEAL
  • Sovereign SDK
  • Web3
  • Blockchain Development

Cloud & DevOps

  • AWS
  • Docker
  • Git
  • Linux
  • Debian
  • Arch Linux

Development Approach

I approach software development with a focus on clean code, scalable architecture and user-centred design. My experience spans .NET, React and Python engineering through to web application penetration testing, so I think about how systems break as well as how they are built.

My Work

Featured Projects

Professional Experience

From internships to software engineering and security consulting

February 2026 — Present

Associate Cyber Security Consultant

MWR CyberSec

Running black-box web application penetration tests across client engagements, from reconnaissance and enumeration through exploitation to the client-facing findings and remediation reports.

Penetration TestingBurp SuiteNmapGobusterNiktoHashcat
June 2025 — September 2025

Software Developer

Veritas Network

Built the frontend architecture for a decentralised truth-finding platform in Next.js, React, TypeScript and Tailwind CSS, shipped as a PWA, and the backend architecture on a Sovereign SDK rollup.

Next.jsReactTypeScriptTailwind CSSPWASovereign SDK
October 2024 — April 2025

Machine Learning Research Resident

Reama AI

Trained Llama models and built RAG pipelines with Hugging Face and pgvector for renewable-energy applications, containerised with Docker.

LlamaRAGHugging FacepgvectorDocker
Let's work together

Haveaprojectinmind?Let'sbringittolife.

I'm always open to discussing new projects, creative ideas, or opportunities to be part of your vision.