AI Engineering Team Leader

XTB is a global company from the financial industry, focusing on online trading of financial instruments. It is the largest FinTech in Poland and a leader in Central and Eastern Europe, operating in several countries including Asia and South America. XTB offers opportunities for employee development through various training and development programs.

• 7+ years of experience in software engineering and AI/ML, including delivering commercial AI solutions end-to-end in production.
• 2+ years in a technical leadership role with responsibility for technical direction and team effectiveness.
• Hands-on experience designing, building, and scaling LLM-based and agentic systems for business use cases.
• Strong architectural background to define and evolve technical vision across AI initiatives.
• Experience building AI platforms or shared AI capabilities for organizations.
• Deep understanding of Python and experience building production-grade APIs and services in cloud environments (Azure, GCP, AWS).
• Expertise with frameworks and tools such as LlamaIndex, LangGraph, PydanticAI, FastAPI, vector databases, and observability stacks.
• Practical experience with LLMOps and MLOps practices including model and prompt versioning, CI/CD, evaluation pipelines, and monitoring.
• Experience implementing evaluation-driven development with measurable quality gates for AI systems.
• Experience embedding AI and automation into business processes with understanding of agentic workflows.
• Ability to translate ambiguous concepts into structured execution plans and lead cross-functional projects.
• Strong understanding of technical debt management and platform evolution.
• Experience mentoring engineers and building a culture of ownership and continuous improvement.
• Excellent communication skills in English for cross-functional collaboration and external representation.

Nice to have:

• Experience in fintech, trading platforms, market data systems, risk-related or regulated domains.
• Experience building Model Context Protocol (MCP) servers and exposing enterprise tools to AI agents.
• Understanding of AI-ready data architecture and enterprise data platforms like Snowflake or Databricks.
• Experience with AI-assisted engineering workflows using tools like Claude Code, Cursor, or GitHub Copilot.
• Familiarity with latency and cost optimization techniques for AI workloads.
• Experience speaking at conferences or publishing technical content.

• Lead and grow a high-performing AI Engineering team, building a transparent, collaborative, high-performance culture focused on delivering end-to-end AI solutions across architecture, backend services, data access layers, evaluation, observability, and production operations.
• Own the technical vision for XTB’s AI ecosystem, aligning it with the company’s evolving product, operational, and regulatory needs.
• Drive architectural decisions across LLM platforms, RAG systems, agentic workflows, automation layers, and internal AI capabilities.
• Remain hands-on by contributing to components, supporting implementations, conducting code reviews, and helping the team make technical decisions.
• Translate abstract ideas and strategic bets into concrete technical plans, action points, and implementation roadmaps.
• Take ownership of the AI technical roadmap, managing architectural coherence, platform evolution, and technical debt.
• Design, guide, and scale resilient end-to-end AI systems for commercial use cases, ensuring production readiness, observability, security, and measurability.
• Drive engineering standards and best practices for LLMOps, AgentOps, deployment, evaluation-driven development, prompt and tool orchestration, and full-stack observability.
• Partner with Product, Data, Platform, Security, and other teams to define AI-ready requirements and ensure shared AI capabilities.
• Support team operational effectiveness by removing blockers and improving workflows.
• Educate other teams on effective AI adoption by creating technical standards and reviewing solution approaches.
• Represent XTB externally by presenting technical solutions and engineering practices at conferences and industry events.
• Contribute to the company’s broader technology vision by building reliable, high-performance AI systems with attention to governance, security, resilience, latency, and operational predictability.