Programming & Backend
Python, SQL, JavaScript, FastAPI, Django, Flask, REST APIs, production backend architecture
About
Novi Pazar, Serbia | +381 62 266996 | resadspahovic94@gmail.com | LinkedIn: Resad Spahovic | GitHub: resadsp | resadspahovic.com
Python Engineer | AI Systems Engineer | Backend, Data & ML Infrastructure
Experienced in building production-ready Python services, ML workflows, LLM/RAG pipelines, and data platforms with measurable impact across multiple industries.
- Birthday: 17 January 1994
- Phone: +381 62 266996
- Location: Novi Pazar, Serbia
- Age: 32
- Degree: Master's Degree
- Website: resadspahovic.com
Focus
AI Systems
Production Python services, ML workflows, LLM/RAG pipelines, and trusted retrieval systems.
Impact
Measured Delivery
Built systems for 50,000+ daily users, cut a nightly pipeline from 4 hours to 45 minutes, and now run my own healthcare software company.
Domains
Cross-Industry Experience
Healthcare, legal tech, agriculture, datacenter operations, analytics, and technical education.
Professional Summary
Python Engineer with 4+ years of experience specializing in AI systems, backend development, data engineering, and ML infrastructure.
Experienced in building production-ready Python services, ML workflows, LLM/RAG pipelines, and data platforms across healthcare, legal tech, agriculture, datacenter operations, and analytics. For the past two years I have designed and built a clinic management system that covers an entire healthcare provider — scheduling, records, laboratory, operating theatre, home visits, stock and finance — and I now run it as my own company, MAAT INNOVATIONS. Alongside it: applications serving 50,000+ daily users and data pipelines rewritten from 4 hours down to 45 minutes.
50,000+
Daily active users served by ML-powered applications.
8
Clinic modules in one system — from booking to profit per department.
4h to 45m
Optimized data processing pipelines for faster operational delivery.
90+
Database migrations behind the clinic platform, every one reversible.
Core Technical Stack
The site content below follows the same categories and technologies listed in the CV.
AI / Machine Learning
TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, OpenCV, NLP, Computer Vision, Time-Series Forecasting
LLM / Retrieval
RAG pipelines, embeddings, vector search, pgvector, Qdrant, chatbot-assisted support, trusted retrieval workflows
Databases & Storage
PostgreSQL, MongoDB, Redis, DuckDB, MySQL, SQLite, Qdrant
Cloud & DevOps
AWS, GCP, Docker, Kubernetes, CI/CD, Prometheus metrics, health/readiness endpoints
Security & Data
JWT, RBAC, authentication/authorization, ETL pipelines, audit logs, rate limiting, automated testing, Qdrant
Professional Experience
Each role below follows the scope and achievements listed in the CV.
Founder & Software Engineer
2026 - Present
MAAT INNOVATIONS, Novi Pazar
- Design and write a clinic management system that covers the whole provider, not one department: scheduling, clinical records, laboratory (LIS), operating theatre, home visits, stock, equipment and finance. See it in use →
- Own every layer: PostgreSQL schema and Alembic migrations, FastAPI services, access control across eight roles, encryption of personal and medical fields at rest with blind-index search, PDF reports, e-mail and SMS.
- Integrations where they matter: laboratory analysers over ASTM, FHIR R4 export, fiscal receipts (ESIR / eFaktura).
- Built the in-house assistant that answers patients from the clinic's own data — local embeddings inside the provider's own database, no external LLM API, and no confident answer to a question the data cannot support.
- Every defect found becomes a regression test that must fail on the old code before the fix lands; the suite runs in CI on every push.
Python Engineer
2024 - Present
LINK Group, Belgrade
- Architected and deployed ML-powered applications serving 50,000+ daily active users, and rewrote the data pipelines behind them — a nightly run went from 4 hours to 45 minutes.
- Led development of a predictive analytics platform for higher-quality operational and business decisions.
- Optimized production data pipelines for faster and more reliable analytics delivery.
- Mentored 5 junior developers and introduced best practices for ML model deployment.
- Introduced automated testing in CI, so a broken pipeline is caught before it reaches a client dashboard rather than after.
Python Programming and Machine Learning Instructor
2022 - 2023
Center NIT
- Designed and delivered Python and Machine Learning curriculum for 200+ students.
- Built hands-on projects simulating real-world industry challenges across Python, ML, and data workflows.
- Created an automated assessment tool that took routine grading off the instructors.
- Built hands-on projects modelled on real industry work across Python, ML and data workflows.
System Administration
2019 - 2022
City of Novi Pazar
- Managed IT infrastructure for 500+ employees across multiple government departments.
- Implemented automated backups with a restore procedure that was rehearsed, not assumed.
- Took part in digital transformation of citizen-facing services.
- Developed internal Python tools to automate routine administrative workflows.
Private Instructor - Mathematics and Computer Science
2017 - 2019
Belgrade
- Provided personalized instruction to 100+ students in advanced mathematics and programming.
- Developed custom learning materials and interactive coding exercises.
- Developed custom learning materials and interactive coding exercises.
Selected Projects
Project descriptions and technologies aligned to the selected projects section from the CV.
Clinic Management System — MAAT INNOVATIONS
One system for an entire healthcare provider rather than one department: scheduling, clinical records, laboratory, operating theatre, home visits, stock, equipment and finance — my own product, sold as MAAT INNOVATIONS.
- Access control across eight roles, patient data encrypted at rest and searched through blind indexes, an append-only audit trail on every read of a medical record, and integrations over ASTM, FHIR and fiscal receipts.
- Key technologies: FastAPI, PostgreSQL, SQLAlchemy, Alembic, JWT, Docker, HTML, CSS, JavaScript, pgvector, Qdrant.
- Business value: one set of numbers across reception, doctors, laboratory and management — nothing entered twice, nothing corrected silently.
Predictive Analytics Platform
Developed an AI-powered predictive analytics platform for historical data analysis, trend forecasting, anomaly detection, and customer behavior analysis.
- Designed ETL workflows with Pandas, NumPy, and Apache Spark, integrated multiple databases, and delivered dashboard reporting with Dash/Plotly.
- Key technologies: FastAPI, TensorFlow, PyTorch, Pandas, NumPy, Apache Spark, PostgreSQL, MongoDB, DuckDB, Dash/Plotly.
- Business value: automates insight generation and improves decision quality through data-backed forecasting.
AI Legal Assistant Platform
Designed an AI legal support platform focused on document understanding, trusted retrieval, and guided assistance workflows.
- Structured around legal document processing, backend services, retrieval pipelines, and user-facing assistant logic.
- Key technologies: AI retrieval workflows, backend services, legal document processing, RAG, vector search, Qdrant, assistant logic.
- Business value: improves information access and helps users navigate document-heavy legal workflows more efficiently.
Drug Interaction Risk Analysis
Created an AI-based system to identify potential drug interactions and predict adverse effects across combined medication use.
- Applied machine learning and NLP techniques for medical text understanding, risk assessment, and safer recommendation workflows.
- Key technologies: Flask, FastAPI, Scikit-learn, TensorFlow, PostgreSQL, spaCy, NLTK.
- Business value: supports pharmaceutical safety, reduces patient risk, and improves medical decision support.
Early Detection of Grapevine Diseases
Developed an AI-powered solution for detecting subtle changes in grapevine leaves and predicting possible plant diseases.
- Implemented deep learning workflows for leaf pattern analysis and used database storage for scalable agricultural monitoring.
- Key technologies: PyTorch, NumPy, Matplotlib, MySQL, Flask.
- Business value: helps vineyards reduce crop loss, improve disease management, and increase yield efficiency.
Datacenter Management API
Developed a REST API for managing datacenter devices and racks with rack-unit capacity validation, power consumption checks, and balanced placement proposals.
- Implemented JWT authentication, RBAC, audit logging, health/readiness endpoints, metrics, rate limiting, optimistic locking, and idempotency support.
- Key technologies: FastAPI, SQLAlchemy, SQLite/PostgreSQL, Docker, JWT, RBAC, Prometheus metrics, audit logs.
- Business value: improves asset control, enforces infrastructure constraints, strengthens traceability, and supports reliable operational decisions.
Education & Certifications
Academic background and certifications presented in the same order as in the CV.
Master's Degree in Computer Science and Mathematics
2022 - 2024State University of Novi Pazar
AI & Python Development
2023 - 2024ITAcademy by LINKGroup, Belgrade
Full-Stack Web Development
2022 - 2023Center NIT, Novi Pazar
State Professional Exam
2021Ministry of Public Administration and Local Self-Government
Bachelor's Degree in Computer Science and Mathematics Education
2012 - 2017State University of Novi Pazar
Computer and Electrical Technician
2008 - 2012Technical School of Novi Pazar
Certifications
- AI & Python Development - ITAcademy by LINKGroup, Belgrade - 2023 - 2024
- Full-Stack Web Development - Center NIT, Novi Pazar - 2022 - 2023