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AI Engineer

📅 Aug 20
📍 🇵🇱 Warsaw - Remote🎹 Mid-level🤖 AI Engineer💼 Full-Time
AI EngineeringGenai SystemsLLM PipelinesAPI Development
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📜 Description

  • 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 (gRPC, MCP) to expose AI capabilities to our global trading platform and internal business units.
  • Measure comprehensive agent performance by combining LLMOps standards (agent tracing), MLOps practices (automated evaluations), and foundational engineering metrics like latency and error rates.
  • Apply evaluation-driven development practices using frameworks like RAG-eval, LLM-as-a-judge techniques, and model benchmarking to optimize system performance.
  • Collaborate with Product and Data teams to build and maintain MCP servers and data-serving layers for AI agents.

🛠️ 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, combined with a 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 to expose internal tools and data to AI agents.
  • Practical experience with LLM orchestration and data frameworks such as LangGraph, or LangChain.
  • Experience in building and maintaining production grade APIs (REST, gRPC, and MCP)
  • Solid understanding of database technologies (PostgreSQL), vector databases (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 the ability to collaborate effectively in an Agile, cross-functional environment in English.
  • Strong understanding of engineering best practices, with hands-on experience in monitoring application health and performance using Prometheus and Grafana.
  • Hands-on experience in AI Agent evaluation, bridging classic ML practices, such as datasets curation and statistical metrics with confidence intervals with GenAI best practices, including LLM-as-a-judge calibration.

✨ 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.
Full job description

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 Engineers and the PdMs 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.

Responsibilities

  • 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 (gRPC, MCP) to expose AI capabilities to our global trading platform and internal business units.
  • Measure comprehensive agent performance by combining LLMOps standards (agent tracing), MLOps practices (automated evaluations), and foundational engineering metrics like latency and error rates.
  • Apply evaluation-driven development practices by using frameworks like RAG-eval, LLM-as-a-judge techniques, and model benchmarking to systematically optimize system performance for both quality and latency.
  • 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 unit tests, tools like linters and type-checkers, documentation, and active participation in code reviews.
  • Leverage agentic coding tools (Claude Code, Codex) in your daily workflow to maximize engineering efficiency and share learnings with the team.

    • 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, combined with a 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 to expose internal tools and data to AI agents.
  • Practical experience with LLM orchestration and data frameworks such as LangGraph, or LangChain.
  • Experience in building and maintaining production grade APIs (REST, gRPC, and MCP)
  • Solid understanding of database technologies (PostgreSQL), vector databases (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 the ability to collaborate effectively in an Agile, cross-functional environment in English.
  • Strong understanding of engineering best practices, with hands-on experience in monitoring application health and performance using Prometheus and Grafana.

    • Nice to have

  • Hands-on experience in AI Agent evaluation, bridging classic ML practices, such as datasets curation and statistical metrics with confidence intervals with GenAI best practices, including LLM-as-a-judge calibration.
  • Knowledge of financial systems, trading, or experience in a regulated fintech environment.
  • Hands-on experience in securing AI applications through LLM red teaming, adversarial testing, and enforcing strict anti-jailbreak policies.
  • Familiarity with cost and latency optimization techniques, such as context compression and prompt caching.

    • What we offer

  • 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.

    • Benefits

  • 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.
    • Apply Now

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