Are you passionate about moving beyond traditional data science to build truly intelligent and autonomous systems? We are looking for a creative and hands-on AI Engineer / Data Scientist to join our team and build the next generation of AI-powered solutions. 
In this role, you will tackle a diverse range of challenges, from developing classic machine learning models for fraud and risk detection to engineering sophisticated AI agents that automate complex business processes. You will have the opportunity to work with cutting-edge tools like LangChain and LangGraph, build agents that interact with the real world, and see your creations come to life in a production environment. If you are a strong Python developer with a love for data and a desire to build the future, this is the role for you. 
 
What You'll Do (Key Responsibilities) 
Develop Autonomous AI Agents: Design and build intelligent agents capable of automating complex business workflows. This includes creating agents that can interact with external APIs, internal tools, and web platforms to accomplish specific goals. 
Build & Deploy Machine Learning Models: Take ownership of the end-to-end lifecycle for our predictive models. You will apply your skills to critical areas like fraud detection, anomaly detection, and risk scoring, moving from data exploration to a deployed production model. 
Automate Analytics & Insights: Create intelligent, data-native agents that can query our databases (like ClickHouse), synthesize information, and automate the creation of analytics dashboards in BI tools such as Metabase. 
Enhance Business Systems: Apply Natural Language Processing (NLP) and agentic workflows to enhance our internal systems, such as customer support and ticketing, to improve efficiency and user experience. 
Productionize AI Solutions: Collaborate with the team to serve your models and agents as robust APIs, ensuring they are scalable and reliable. 
 
What We're Looking For:

Strong Python Proficiency: You have mid-level software engineering skills and can write clean, efficient, and production-ready Python code. 
Experience Building with LLMs: You have hands-on experience building applications or agents using modern AI frameworks like LangChain, LangGraph, or similar tools. 
LLM Knowledge: You are familiar with the large language model ecosystem, understand the differences between major models, and know about concepts like quantization. 
Machine Learning Fundamentals: You possess a solid understanding of both classic machine learning (e.g., classification, regression) and deep learning concepts. 
Problem-Solving Mindset: You are passionate about using your data science skills to solve real-world business problems in a collaborative team environment. 
Familiarity with Data Tooling: You have experience with workflow orchestration tools (Apache Airflow or similar) and data visualization platforms (Metabase, Tableau, etc.). 
Model Evaluation: You know how to design experiments and implement robust evaluation frameworks to measure the performance of your AI models and agents. 

Bonus Points:

Experience with Django or another web framework for deploying ML models. 
Hands-on experience with ClickHouse or other OLAP databases. 
You've deployed models or agents in a production environment before.