AI Engineer

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 Product Managers 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 the global trading platform and internal business units.
• Measure agent performance using LLMOps standards such as agent tracing, MLOps practices including automated evaluations, and engineering metrics such as latency and error rates.
• Apply evaluation-driven development using RAG-eval, LLM-as-a-judge techniques, and model benchmarking to optimize quality and latency.
• Collaborate with Product and Data teams to build and maintain MCP servers and data-serving layers that provide AI agents with real-time enterprise data.
• Maintain code quality through unit tests, linters, type-checkers, documentation, and code reviews.
• Use agentic coding tools, including Claude Code and Codex, to improve engineering efficiency and share learnings with the team.

Requirements

• 2–5 years of commercial experience in AI/ML or software engineering, with a proven record of deploying systems to production.
• Ability to write modern, Pythonic code and solid understanding of AI agent architectures, including context engineering, tool calling, skills, and agent loops.
• Hands-on expertise developing Model Context Protocol (MCP) servers or custom tool-calling interfaces that expose internal tools and data to AI agents.
• Practical experience with LLM orchestration and data frameworks such as LangGraph or LangChain.
• Experience building and maintaining production-grade REST, gRPC, and MCP APIs.
• Solid understanding of PostgreSQL, pgvector, and advanced search strategies—semantic, hybrid, and BM25—for AI agents.
• Familiarity with MLOps/LLMOps, including basic observability with MLflow or Langfuse, automatic evaluations, and prompt optimization.
• Strong communication skills and ability to collaborate in an Agile, cross-functional English-speaking environment.
• Strong understanding of engineering best practices and hands-on experience monitoring application health and performance with Prometheus and Grafana.

Nice to have

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

What we offer

• Real influence on company and product development.
• Work in an experienced team that shares knowledge.
• Regular feedback and clear career paths.
• Regular team-building meetings.

Benefits

• Training budget for courses and conferences.
• 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 English learning and a benefits platform.
• Access to a wellbeing platform, workshops, and private therapy sessions.
• Remote work, work from the Warsaw office, or from a coworking space in your city.