Senior AI Engineer

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.

As a Senior AI Engineer, you will be the technical authority for our LLMOps and Agentic strategy. We are moving beyond prototypes to build resilient, enterprise-grade systems where evaluation-driven development and full-stack observability are core requirements, not afterthoughts. You will ensure XTB’s ecosystem remains at the forefront of innovation-delivering secure, measurable, and highly reliable experiences for over 1 million investors worldwide.

Responsibilities

• Design and scale resilient, end-to-end architectures for LLM and agentic solutions within a high-load, low-latency fintech environment.

• Act as a strategic technical partner to the Head of AI, leading architectural reviews and Buy vs Build analyses for greenfield AI projects.

• Take full ownership of the AI product lifecycle, establishing rigorous standards for LLMOps, FinOps, and automated deployment pipelines from PoC to production.

• Spearhead the adoption of Agentic Evals and RAG-eval frameworks to turn fine-grained observability signals into actionable system improvements.​

• Collaborate with Data and Product teams to architect AI-ready data layers and MCP servers, ensuring seamless agentic access to semantic layers in Snowflake and Databricks.

• Foster a culture of technical excellence by mentoring engineers and defining best practices for AI-assisted development (Claude Code, Cursor) to elevate team productivity.

• Bridge technical complexity with business ROI, ensuring all solutions adhere to financial AI Governance and security standards.

Requirements

• 5+ years of experience in architecting and deploying production-grade AI/ML solutions Azure, GCP, or AWS ecosystems, underpinned by a mastery of Python and a solid foundation in the full ML lifecycle (from classical statistical models to deep learning and NLP).

• Deep hands-on expertise with LLM orchestration and data frameworks like LlamaIndex, LangGraph, or PydanticAI and building complex, multi-step agentic workflows.

• Practical experience in developing and deploying Model Context Protocol (MCP) servers to expose enterprise tools and internal data to AI agents.​

• Strong background in MLOps and LLMOps pipelines, including model versioning, automated deployment, and full-stack observability for both deterministic and agentic services.

• Practical experience in implementing evaluation-driven development using frameworks like RAG-eval and agentic evaluations to measure reasoning and tool-calling accuracy.​

• Proficiency in building high-performance APIs with FastAPI and designing semantic layers on top of enterprise data platforms such as Snowflake or Databricks, integrated with vector databases (e.g., Weaviate, pgvector).

• Ability to perform Buy vs Build analyses and translate business requirements into technical architectures that balance innovation with ROI and FinOps.

• Experience in leading technical initiatives, conducting rigorous code reviews, and mentoring other engineers to foster a culture of excellence.

• Excellent communication skills and the ability to work cross-functionally with data engineers and product managers in English.

Nice to have:

• Mastery of Claude Code, Cursor, or GitHub Copilot and a track record of implementing AI-assisted engineering best practices.​

• Previous experience in fintech, specifically within trading platforms, risk modeling, or high-frequency data environments.

• Familiarity with Small Language Models (SLM) and techniques for strategic cost and latency optimization.

• Solid understanding of Data Engineering fundamentals, including Spark, Kafka, and modern Lakehouse architectures.

What we offer

• Real impact 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.

• 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.

• Regular team-building meetings.