AI Engineer (Genai, Autonomous Agents & Operations Ai)

QLTEQ TEKNOLOJİ YAZILIM DANIŞMANLIK ANONİM ŞİRKETİ

AI Engineer (GenAI, Autonomous Agents & Operations AI)

Location: [İstanbul / Hybrid / Remote] 

At QLTEQ we are building the autonomous backbone of global logistics and supply chain automation. We engineer production AI systems that optimize fleet movements, parse logistics documents, and translate natural language into real-time database queries. 

We are looking for a hands-on AI Engineer who loves writing clean code and solving real-world problems to contribute to our Generative AI, autonomous agent, and operational optimization projects.

What You’ll Do ; 

• AI Agents & MCP Development: Build and maintain Model Context Protocol (MCP) 

services that securely connect AI agents (Claude, Gemini, OpenAI) to our internal 

databases and APIs. 

• Text-to-SQL & RAG Pipelines: Develop and improve natural language-to-SQL 

systems (MSSQL, pgvector) that translate user questions into accurate, safe 

database queries. 

• Intelligent Document Processing: Extract structured data (using Pydantic) from 

freight documents (invoices, bills of lading, delivery proofs) using multimodal vision 

models (Gemini) and OCR pipelines. 

• Optimization & Machine Learning: Contribute to training, deploying, and 

maintaining ML and optimization models for driver dispatching, route planning, and 

rate/ETA predictions. 

• Evaluation & Backend Services: Write automated evaluation scripts to test LLM 

accuracy and support asynchronous background services using Celery, RabbitMQ, 

and Redis. 

What We’re Looking For ;

• Experience: 2–3 years of hands-on experience in software engineering, data science, or AI engineering (ideally having deployed at least one LLM, RAG, or ML project to production). 
•  Python Proficiency: Strong command of Python and modern libraries (FastAPI, Django/Flask, Pydantic, Pandas, Scikit-learn). 
• GenAI & LLM Tooling: Practical experience building with OpenAI, Gemini, or Claude APIs, RAG architectures, vector databases, and frameworks like LangChain. 
• Databases: Solid SQL skills (preferably MSSQL and PostgreSQL / pgvector) and familiarity with ORMs (SQLAlchemy, etc.). 
• Modern Workflow: Familiarity with Docker and Git, plus active daily use of AI coding assistants (Cursor, Claude Code, or GitHub Copilot). Nice to Have (Bonus Points): 

Nice to Have (Bonus Points):

• Experience with Celery, RabbitMQ, Redis, or Microsoft Azure. 
• Interest or background in logistics, route optimization (e.g., OR-Tools), or computer vision (OCR / OpenCV). 

You don’t need to check every single box on this list. If you have a strong Python foundation, stay on top of the latest LLM/Agent technologies, and are excited to build AI systems that run in the real world, we’d love to hear from you!