Available for opportunities

Hello, I'm David Kitunov

Aspiring DevOps Engineer & Software Developer

Third-year Computer Science student focused on reliability, observability, and practical software delivery. Currently working as a NOC Engineer at Ness, improving incident quality and operational stability.

CS
Student (3rd Year)
3+
Live Projects
NOC
Engineer @ Ness

About Me

I'm a dedicated Computer Science student on a mission to become a DevOps Engineer. My journey in tech started with a curiosity for how things work behind the scenes, which led me to explore both software development and infrastructure.

Recently, I joined Ness as a NOC Engineer, where I'm gaining hands-on experience with monitoring systems, incident response, and infrastructure management. This role is strengthening my foundation in operations while I continue to develop my automation and cloud skills.

I'm passionate about bridging the gap between development and operations, building CI/CD pipelines, containerization with Docker, and creating efficient, scalable systems.

Name David Kitunov
Email kitunovdavid57@gmail.com
Current Role NOC Engineer @ Ness
Goal DevOps Engineer
Let's Connect

Technical Skills

Technologies and tools I work with

DevOps & Cloud

Building and automating infrastructure with modern tools

Docker CI/CD Git Linux Monitoring

Frontend Development

Creating modern, responsive user interfaces

React Next.js JavaScript Tailwind CSS

Backend Development

Building scalable server-side applications

Node.js Express Python REST APIs

ML & Computer Vision

Real-time models with lean inference pipelines

TensorFlow MediaPipe OpenCV Python Kaggle

Databases

Working with various database technologies

MySQL MongoDB Firebase Mongoose

Programming Languages

Core languages for software development

Python JavaScript Java C C++ SQL

NOC & Operations

Infrastructure monitoring and incident management

CheckMK Monitoring Incident Response Linux Networking

How I Work

My process for shipping reliable software and operations improvements

01

Observe and Frame

I start with signals: logs, alerts, failure reports, and user impact. The first goal is a clear problem statement.

02

Design the Fix

I choose the smallest reliable change first, then define what success looks like before implementation.

03

Ship and Validate

I validate behavior with practical checks, edge-case testing, and simple rollback-safe deployment steps.

04

Document and Improve

Each fix ends with clean notes and follow-up improvements so the same issue is easier to handle next time.

Work Experience

My professional journey

NOC Engineer

Ness Technologies

Jan 2026 - Present
  • Monitoring infrastructure using CheckMK and other alerting tools
  • Responding to incidents and performing root cause analysis
  • Working with Linux servers and network infrastructure
  • Coordinating incident communication and escalation during production issues
  • Maintaining clear runbooks and handover notes for stable operations

Air Force Personnel NCO

IDF Personnel Directorate

2022 - 2025
  • Managed administrative tasks and personnel data for Air Force population
  • Handled documentation, records, and data processing
  • Developed organizational skills and attention to detail
  • Worked in a structured, deadline-driven environment

My Education

Academic background and achievements

B.Sc. Computer Science

Holon Institute of Technology (HIT)

Expected Graduation: 2026

Relevant Coursework

Data Structures & Algorithms Software Engineering Databases Operating Systems Machine Learning Object-Oriented Programming

Featured Projects

Some of my recent work

Brogram - Workout Application
September 2025

Brogram

Problem

Most beginner workout apps feel overloaded and hard to follow daily.

Solution

Built a focused 30-day React program with low-friction UX and clear daily progression.

Result

Delivered a lightweight routine tracker with consistent completion flow.

30-Day Program Mobile First
React Tailwind CSS JavaScript
SignLangModel - ASL Recognition
February 2026

SignLangModel

Problem

Image-based sign recognition can be heavy and unstable across lighting and background changes.

Solution

Used MediaPipe landmarks and a compact TensorFlow model with Kaggle training and webcam inference.

Result

Built a responsive recognizer with reproducible artifacts and a research-ready report.

Model < 1 MB Real-time Inference
TensorFlow MediaPipe OpenCV Python
Stripe Store - E-commerce
October 2025

Stripe Store

Problem

Needed an e-commerce demo that feels production-ready, not just a static storefront.

Solution

Built a Next.js storefront with Stripe payments, clear catalog flow, and secure checkout path.

Result

Shipped an end-to-end demo that covers browsing, cart state, and payment completion.

Stripe Checkout Next.js App
Next.js Stripe Tailwind CSS

Get In Touch

Let's connect and discuss opportunities

I'm currently looking for DevOps and software development opportunities. Whether you have a question or just want to say hi, feel free to reach out!