AI/ML Engineer (Gen AI +/- MLOps)

We are developing a central competency team dedicated to artificial intelligence engineering. In connection with new implementations planned for the upcoming year, we are looking for AI/ML engineers who combine competencies in the field of Generative AI and MLOps (or demonstrate strong specialization in one of these areas with a willingness to develop in the other).

You will co-create universal modules, engineering accelerators, and production agentic and LLM systems, implemented in modern technological solutions.

Daily tasks

• Building and scaling reusable components, AI services, and reusable libraries for related products.
• Designing and implementing production architectures based on Generative AI: retrieval pipelines (RAG), tool use, orchestration layers, and agentic workflows.
• Implementing evaluation loops (evaluation-driven development) monitoring quality, latency, costs, grounding, and model robustness.
• Creating technical specifications, interface definitions, data flow contracts, and testing frameworks.
• Implementing observability, monitoring, governance, and security standards for AI solutions in a cloud environment.
• Rapid prototyping (PoC) of innovative technological approaches and translating them into stable production components.
• Collaborating with product teams (AI PM/PO, software engineers) on the integration of central AI capabilities.

Requirements

• Min. 3 years of commercial experience in software engineering, including designing AI systems or data-intensive solutions for production environments.
• Very good knowledge of Python and modern libraries of the AI/ML ecosystem.
• Practical experience with Generative AI solutions (LLM, RAG, tool calling, multi-agent systems) along with an understanding of their limitations, costs, and failure modes.
• Experience with public cloud — Azure preferred (knowledge of GCP or AWS will be an additional asset).
• Understanding of MLOps / LLMOps best practices: model deployment, CI/CD pipelines, quality evaluation, and test automation.
• Ability to create clear architecture, specifications, and integration interfaces.
• Higher education in a relevant field (Computer Science, AI, Data Science, or related) or equivalent project experience.
• Fluent communication in English (working in an international environment).

Must have: AI, Python, ML, LLM, RAG, Azure, GCP, AWS, MLOps, CI/CD, Data science