AI Engineer

O projekcie: XTB is a global company from the financial industry, focusing on online trading of financial instruments. We are the largest FinTech in Poland and a leader in Central and Eastern Europe, and the range of our operations covers several countries, including Asia and South America. At XTB, we focus on the development of our employees, giving them opportunities to gain knowledge and skills in various fields, as well as offering a number of training and development programs. If you are looking for challenges and want to gain valuable experience in an international business environment, XTB is the right place for you. We are a certified Great Place to Work company. We are looking for an AI Engineer with a passion for building production-grade GenAI systems. In this role, you will work closely with Senior Engineers and the Head of AI to implement, deploy, and scale advanced LLM and agentic solutions. This is an opportunity for an engineer who values engineering excellence and wants to see their code impacting millions of investors in a high-stakes fintech environment. Wymagania: - 2-5 years of commercial experience in AI/ML or Software Engineering, with a proven track record of deploying systems to production. - Proficiency in Python and a solid understanding of the full ML lifecycle, from data preparation to model deployment and monitoring. - Hands-on expertise in developing Model Context Protocol (MCP) servers or custom tool-calling interfaces to expose internal tools and data to AI agents. - Practical experience with LLM orchestration and data frameworks such as LlamaIndex, LangGraph, or LangChain. - Experience in building and maintaining RESTful APIs using FastAPI in a cloud-native environment (Azure, GCP or AWS). - Solid understanding of database technologies, including hands-on experience with vector databases like Weaviate or pgvector. - Familiarity with MLOps/LLMOps concepts, including CI/CD pipelines, containerization (Docker), and basic observability. - Analytical mindset with the ability to debug complex issues in non-deterministic AI systems.​ - Strong communication skills and the ability to collaborate effectively in an Agile, cross-functional environment in English. Nice to have: - Hands-on experience with evaluation frameworks (e.g., Langfuse, LangSmith) and observability tools.​ - Knowledge of financial systems, trading, or experience in a regulated fintech environment. - Solid understanding of Data Engineering fundamentals, including Spark, Kafka, and modern Lakehouse architectures built on platforms like Snowflake or Databricks. - Familiarity with Small Language Models (SLM) and techniques for strategic cost and latency optimization. - Proficiency in using AI-assisted development tools like Claude Code, Cursor, or GitHub Copilot. Codzienne zadania: - Implement and maintain end-to-end AI solutions, focusing on the robustness and scalability of LLM pipelines and agentic workflows. - Develop and optimize RAG systems and AI agents using modern frameworks, ensuring high-quality retrieval and response accuracy. - Build and integrate production-grade APIs (FastAPI) to expose AI capabilities to our global trading platform and internal business units. - Participate in the implementation of LLMOps and MLOps standards, including automated testing, model versioning, and full-stack observability. - Apply evaluation-driven development practices by using frameworks like RAG-eval to systematically measure and improve system performance.​ - Collaborate with Product and Data teams to build and maintain MCP servers and data-serving layers that empower AI agents with real-time enterprise data. - Maintain high code quality through rigorous testing, documentation, and active participation in code reviews. - Leverage agentic coding tools (Claude Code, Cursor) in your daily workflow to maximize engineering efficiency and share learnings with the team.