AI Engineer
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Job Description
AI Engineer building production-grade LLM, RAG, and agentic systems for XTB’s global online trading platform. Deploying scalable APIs and evaluation-driven AI solutions impacting millions of investors.
Responsibilities:
- Implement and maintain end-to-end AI solutions, focusing on robust and scalable LLM pipelines and agentic workflows
- Develop and optimize RAG systems and AI agents using modern frameworks
- Build and integrate production-grade APIs (gRPC, MCP) for the global trading platform and internal business units
- Measure agent performance using agent tracing, automated evaluations, latency, and error-rate metrics
- Apply evaluation-driven development with RAG-eval, LLM-as-a-judge techniques, and model benchmarking
- Collaborate with Product and Data teams to build and maintain MCP servers and data-serving layers with real-time enterprise data
- Maintain code quality through unit tests, linters, type-checkers, documentation, and code reviews
- Use agentic coding tools such as Claude Code and Codex to maximize engineering efficiency and share learnings
Requirements:
- 2-5 years of commercial experience in AI/ML or Software Engineering, with a proven track record of deploying systems to production
- Ability to write modern, Pythonic code
- Solid understanding of AI Agent architectures, including context engineering, tool calling, skills and agent loops
- Hands-on expertise in developing Model Context Protocol (MCP) servers or custom tool-calling interfaces
- Practical experience with LLM orchestration and data frameworks such as LangGraph or LangChain
- Experience building and maintaining production-grade APIs (REST, gRPC, and MCP)
- Solid understanding of PostgreSQL, pgvector, and advanced search strategies (semantic, hybrid, BM25) for AI Agents
- Familiarity with MLOps/LLMOps concepts, including basic observability (MLflow or Langfuse), automatic evaluations, and prompt optimizations
- Strong communication skills and ability to collaborate effectively in an Agile, cross-functional environment in English
- Strong understanding of engineering best practices
- Hands-on experience monitoring application health and performance using Prometheus and Grafana
- Nice to have: hands-on experience in AI Agent evaluation, financial systems/trading or regulated fintech, AI security and red teaming, adversarial testing, anti-jailbreak policies, cost and latency optimization, context compression, and prompt caching
Benefits:
- Real influence on the development of the company and the product
- Work in an experienced team that is happy to share its knowledge
- A clear vision of development thanks to regular feedback and clear career paths
- Regular team-building meetings
- A training budget for courses and conferences that interest you
- An extra day off on your birthday
- An extra day off for parents
- Equipment tailored to your needs
- Private medical care and group insurance
- Access to an e-learning platform for learning English and a benefits platform
- Access to a wellbeing platform and the opportunity to take advantage of workshops and private therapy sessions
- Remote work, from the office in Warsaw or from a coworking space in your city
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