$whoami
Ismat Samadov
AI & Full-Stack Engineer
# Currently AI Engineer at PASHA Real Estate
Focused on applied AI — RAG & document systems
- Location
- Baku, Azerbaijan
- Work mode
- Remote & on-site
I build retrieval-augmented generation and document-AI systems, and the web apps and data pipelines they run on. Six years working with data across banking and analytics, now focused on applied AI. MBA in Artificial Intelligence.
$ catexperience.log
8 roles
- Building LLM-powered AI agents to extract and process information from contracts, tender documents, and reports
- Designing and deploying AI assistants supporting legal, procurement, and construction departments
- Developing and optimizing Retrieval-Augmented Generation (RAG) pipelines for precise document analysis
- Building production LLM applications on the OpenAI and Anthropic APIs with a focus on scalability and reliability
- Processing unstructured data from PDFs, spreadsheets, and emails to generate actionable business insights
- Improving AI output quality by reducing hallucinations and integrating solutions with internal data systems
- Python
- LLMs
- RAG
- AI Agents
- Prompt Engineering
- OpenAI
- Anthropic
- LangChain
- Building automated data pipelines and ETL processes for product analytics
- Developing Python scripts for data processing, analysis, and report automation
- Engineering SQL-based analytical solutions for strategic goal monitoring
- Implementing automated reporting systems to replace manual processes
- Building predictive models for market trend analysis and business forecasting
- Architecting data workflows and optimizing query performance for large datasets
- Python
- SQL
- ETL
- Predictive Modeling
- Data Pipelines
- Developed backend services using async Python in a cloud-based, containerized architecture
- Designed and implemented RESTful API endpoints for platform features and data interactions
- Integrated backend services with MongoDB and Redis for efficient data storage and caching
- Built modular and reusable service components aligned with microservice-oriented design principles
- Participated in CI/CD workflows using GitLab for version control, testing, and deployment
- Collaborated in an agile, task-based development environment with rapid iteration cycles
- Worked with Google Cloud infrastructure to support scalable backend operations
- Python
- AsyncIO
- REST APIs
- MongoDB
- Redis
- Docker
- GCP
- GitLab CI/CD
- Designed, built, and run birjob.com, a live job-aggregation platform that consolidates 15,000+ active vacancies from 80+ Azerbaijani employment sites into one free, ad-free search experience
- Own the entire stack end to end — Next.js/React frontend, backend APIs, data layer, and cloud deployment — shipping from architecture through production
- Engineered automated scraping and ETL pipelines that crawl 80+ sources every few hours, deduplicate, and index listings in near real time
- Built AI-powered features including an LLM-based CV compatibility checker that scores resumes against job descriptions
- Implemented multi-channel notifications — email subscriptions and a Telegram bot — delivering targeted new-job alerts to subscribers
- Exposed a public REST API and run the full system in production with no registration required and direct redirection to original employer postings
- TypeScript
- Next.js
- React
- Python
- Web Scraping
- ETL
- PostgreSQL
- REST APIs
- LLMs
- Telegram Bot API
- Developed ML-based fraud detection models using Python, scikit-learn, and TensorFlow
- Built and deployed behavioral scoring models for real-time fraud risk assessment
- Engineered feature pipelines for fraud pattern recognition and anomaly detection
- Implemented automated fraud monitoring systems with configurable rule engines
- Designed and optimized SQL queries for fraud investigation workflows
- Built dashboards and alerting systems for fraud trend monitoring
- Collaborated with engineering teams to integrate ML models into production systems
- Python
- scikit-learn
- TensorFlow
- SQL
- Anomaly Detection
- Feature Engineering
- ML Ops
- Built complex SQL queries and stored procedures for data extraction and transformation
- Developed Python automation scripts for data processing and ETL workflows
- Engineered interactive dashboards using BI tools for real-time metrics tracking
- Implemented data validation pipelines for loan performance analysis
- Built automated reporting systems that reduced manual effort by 60%
- SQL
- Stored Procedures
- Python
- ETL
- BI Dashboards
- Reviewed and verified consumer loan applications, making approve/reject decisions based on credit policy
- Assessed applicant creditworthiness by analyzing income, debt, and credit history against lending criteria
- Verified the authenticity of applicant documents and information to detect fraud and misrepresentation
- Conducted phone and database checks to confirm employment, identity, and financial details
- Documented decision rationale and ensured compliance with internal lending regulations
- Loan Underwriting
- Credit Assessment
- Document Verification
- Fraud Detection
Chief of Fuel Service
2 yrsAzerbaijan Air & Air Defense Forces · Full Time · Onsite
Azerbaijan
- Served as Chief Lieutenant, leading the fuel service for an air defense unit
- Managed fuel logistics, storage, and distribution to maintain operational readiness
- Supervised personnel and enforced strict safety and handling procedures for hazardous materials
- Maintained accurate inventory records and ensured compliance with military regulations
- Leadership
- Logistics
- Inventory Management
- Safety Compliance
$ cateducation.log
$ lscertifications/
74 earned
# coursework & micro-credentials — click an issuer to view certificates
DataCamp17
- Data Manipulation in SQL
- Data Manipulation with pandas
- Functions for Manipulating Data in PostgreSQL
- Intermediate Python
- Intermediate SQL Queries
- Introduction to Data Science in Python
- Introduction to Power BI
- Introduction to Python
- Introduction to R
- Machine Learning with scikit-learn
- PostgreSQL Summary Stats and Window Functions
- SQL for Joining Data
- Understanding Cloud Computing
- Understanding Data Engineering
- Understanding Data Science
- Understanding Data Visualization
- Understanding Machine Learning
Coursera9
- Data Analysis with Python
- Generative AI for Everyone
- Generative AI: Business Transformation and Career Growth
- Generative AI: Prompt Engineering Basics
- Introduction to Artificial Intelligence
- Introduction to Business Analytics: Communicating with Data
- Neural Networks and Deep Learning
- Structuring Machine Learning Projects
- What is Data Science
HackerRank3