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DenisXhabrahimi

Software & Data Engineering

DenisXhabrahimi

Specialized in building production software and data-intensive systems, from AI automation and full-stack platforms to distributed and high-performance computing.

  • Production software
  • AI automation
Wanna see what I've built?Contact me
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Data Engineer & Software Developer

MSc · Basel

Denis Xhabrahimi, Software & Data Engineer

Engineered for production

Selected systems

Things I have
actually shipped.

Each one started as a real problem — a workflow held together by spreadsheets, an inbox with no structure, or a compute budget spent on the wrong strategy. Every project has a full case study behind it.

FAB Construction IMS dashboard showing total inventory value, stock levels by category, work-order status and a live low-stock alert list01
Data & Software PlatformsCompleted

Replacing spreadsheet-driven inventory with a centralized operations platform

FAB Construction Inventory Management System

Problem
A construction company tracked stock, tools and job status across spreadsheets and informal messages — so nobody could reliably answer what was in stock, where it was, or which work was blocked.
Outcome
One system for products, multi-location stock, suppliers, stock movements, work processes and role-based access — on the web and as iOS and Android apps for staff working on site.
ReactTypeScriptFastAPIPostgreSQLiOSAndroid
Case studyLive demoSource

Full archive

02

Browse all work →

Track record

Built inside
real organizations.

The systems above came out of the roles here — problems I found while working, not briefs handed to me.

RYCO (Regional Youth Cooperation Office)

Technology Officer

Designed and built an AI-powered IT support agent using Microsoft Copilot Studio and Power Automate, automating conversational ticket intake, categorization, routing and confirmation for RYCO's helpdesk.

AI AutomationChatbot DevelopmentIT SupportMicrosoft 365

FAB Construction

Junior IT Consultant

Deployed an Enterprise Resource Planning (ERP) system and Inventory Management System (IMS), increasing the working environment's efficiency.

ERP SystemsInventory ManagementIT StrategyDisaster Recovery

Earlier

  • Assistant Manager · White Dream Hotel
  • Entry-Level Front-End Developer · AKSHI
Full history and dates

Profile

I build systems for
messy systems.

I build systems for messy systems. Most of my work has begun the same way: an organization with a real operational problem — inventory tracked across spreadsheets and chat messages, IT requests arriving with no structure, compute budgets spent on the wrong parallelization strategy — and no clean specification for how to fix it. My job has been to understand the constraints, design something that fits them, and build it end to end.

Besides my master's in data science, I am always looking for messy systems to build solutions for.

Education
MSc Data ScienceUniversity of Basel
BSc Computer ScienceUNYT, Tirana
Background
4 years in technical rolesIT consulting, operations and engineering
01

Software Engineering

Full-stack and backend systems built end to end — normalized data models, authenticated REST APIs, and interfaces non-technical staff use daily.

02

AI & Automation

Conversational intake and workflow automation that sits inside the tools an organization already uses, plus the applied ML behind it.

Also works across

Applied research

Where the answer is
a measurement.

MSc work where the deliverable was a measured result rather than a shipped platform.

Completed

Privacy-Preserving Machine Learning

How much predictive utility must be sacrificed to achieve meaningful, empirically-verified privacy guarantees when training credit-default models?

My contribution
A team coursework project. My contribution focused on the DP-SGD and Local DP training pipelines, two independent membership-inference attacks across privacy budgets, and the utility-privacy-fairness analysis. Results below are the project's shared findings.
PythonPyTorchOpacusDP-SGDDifferential Privacy

Completed

High-Performance 1D Earth Mover's Distance

How do sequential, shared-memory, distributed-memory and GPU parallelization strategies compare in runtime and energy efficiency for 1D Earth Mover's Distance?

My contribution
A team project across four algorithms. I owned the 1D Earth Mover's Distance workload — sequential, OpenMP, MPI, CUDA and hybrid variants — plus its prefix-scan optimization and the profiling and performance analysis.
C/C++OpenMPMPICUDASlurm

Also covered in coursework

  • Continuous Optimization MethodsPython · NumPy
  • Distributed Information SystemsDistributed Systems · System Design
  • Cloud Messaging Architectures on AWSAWS · Messaging Systems
  • Graph Modeling of Flight-Route DataNeo4j · Graph Databases
All applied research

Toolkit

What tech stack
I have used.

Grouped by how deeply I actually use each one, rather than as one flat list.

Core

01

What I build with by default — each one behind a shipped project on this site.

  • Python
  • TypeScript
  • React / Next.js
  • FastAPI
  • PostgreSQL
  • REST API design
  • Data modeling
  • Docker
  • Git / GitHub Actions

Specialized

02

Narrower contexts, but where the hardest problems I have worked on live.

  • C / C++
  • CUDA
  • MPI
  • OpenMP
  • OpenACC
  • Slurm / HPC clusters
  • Parallel algorithms
  • Rust
  • PyTorch
  • Opacus / Differential Privacy
  • Copilot Studio
  • Power Automate
  • LLM application design

Working knowledge

03

Used in coursework, prototypes or earlier roles — comfortable, not deep.

  • Java / Spring Boot
  • PHP / Laravel
  • Django
  • MongoDB
  • Neo4j / Cypher
  • AWS
  • Azure
  • Microsoft 365
  • Kubernetes
  • Vercel

Contact

Let's build
something
useful.

Hiring for AI, data or platform engineering — or building something technically difficult? Tell me what you are working on.

dxhabrahimi2002@gmail.com
GitHubLinkedInEmailResume
  • AI & data engineering
  • Forward-deployed / customer-facing engineering
  • Applied AI & automation