Senior AI Engineer

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. The company offers training and development programs and values employee growth.

• 4+ years as a Platform Engineer, Backend Engineer, or AI Engineer with hands-on platform/service delivery experience.
• Strong software engineering fundamentals with proficiency in Python and/or Go/Java, clean code practices, and system design.
• Production experience with Kubernetes and ArgoCD for GitOps deployments.
• Expert-level knowledge of GitLab CI/CD including pipeline design, deployment management, and build optimization.
• Practical experience with LLM frameworks and agentic systems such as LangGraph or Pydantic AI.
• Working knowledge of RAG systems including vector databases, similarity search, and prompt engineering.
• Understanding of LLM routing and optimization including cost-aware model selection and multi-model orchestration.
• Experience building or managing gateway/proxy infrastructure like API gateways, reverse proxies, and load balancing.
• Strong foundation in infrastructure-as-code, version control (Git), and CI/CD best practices.
• Excellent communication skills to collaborate with AI/ML teams, data engineers, and product managers.

• Design and implement an enterprise AI platform with LLM-based routing, intelligent model selection, fallback strategies, and cost optimization.
• Build and maintain MCP (Model Context Protocol) gateway infrastructure for integration of enterprise tools and internal data with AI agents.
• Architect LangGraph-based orchestration frameworks for complex agentic workflows.
• Implement RAG platform components including vector search integration, prompt optimization, and chunking strategies.
• Establish observability using tools like Langfuse for tracing, cost monitoring, token usage analytics, and LLM quality metrics.
• Design and optimize APIs for LLM interactions.
• Build deployment and orchestration pipelines using Kubernetes with ArgoCD for GitOps-driven AI service deployments.
• Establish CI/CD infrastructure using GitLab CI/CD for automated testing, deployment, and versioning.
• Implement security, authentication, and rate limiting for AI endpoints ensuring multi-tenant isolation.
• Create self-service developer interfaces and documentation for building agentic applications.
• Lead technical initiatives, conduct code reviews, mentor engineers, and foster an AI-first engineering culture.

Nice to have:

• Experience building prompt management and versioning systems.
• Knowledge of semantic caching or prompt optimization techniques.
• Experience with multi-tenant SaaS architecture or PaaS design.
• Familiarity with evaluation frameworks for LLM outputs or agentic behavior.
• Experience with vector database optimization or semantic search.
• Knowledge of advanced deployment patterns (canary, blue-green, A/B testing) for AI services.