ai engineer for Legal AI

YPOG is a business law and tax advisory firm focused on Legal Tech, Legal AI, and innovation. It develops digital solutions and AI products for modern legal consulting and works to shape the future of the legal market with Generative AI, Machine Learning, and modern software solutions.

• Design, develop, and operate production-ready Legal-AI systems using modern model-independent frameworks and AI best practices;
• Develop Generative-AI and LLM applications, including Retrieval-Augmented Generation (RAG), Agentic-AI, agent and tool-use workflows, and structured information extraction;
• Design data, retrieval, and inference pipelines for complex legal documents and knowledge bases;
• Select and integrate suitable models and providers based on quality, latency, cost, data protection, and operational security;
• Develop robust evaluation and benchmarking frameworks for factual accuracy, retrieval quality, robustness, and reliability;
• Build and maintain test datasets, automated evaluation pipelines, and meaningful quality metrics;
• Analyze failure patterns and systematically optimize prompts, prompt engineering, chunking, retrieval, ranking, tool use, and system architecture;
• Monitor AI systems in production, manage LLMOps, and continuously improve them;
• Collaborate closely with Legal Engineers, Software Engineers, lawyers, Product, and other interdisciplinary teams;
• Document technical solutions and ensure secure, traceable, and responsible AI use;
• Take ownership from the initial hypothesis through prototyping and benchmarking to deployment, monitoring, and continuous improvement.

• Practical experience in AI Engineering, Machine Learning Engineering, Applied AI, Data Science with production responsibility, or a comparable role;
• Very good Python skills and experience with modern AI, Machine Learning, and Generative-AI frameworks and libraries;
• Proven experience building production-ready LLM applications, beyond prompting or prototyping;
• Strong understanding of Retrieval-Augmented Generation (RAG), embeddings, semantic search, vector databases, chunking, ranking, and context management;
• Experience systematically evaluating generative AI systems, including test datasets, quality metrics, automated tests, and human evaluation;
• Clear, open, and solution-oriented communication in German and English;
• Comfortable working in dynamic environments without rigid processes;
• Proactive ownership of projects and features;
• Ability to collaborate across professional disciplines;
• Pragmatic, solution-focused mindset;
• Results-oriented approach with fast iterations and prioritization of important tasks;
• Nice to have: experience with LLMOps, MLOps, tracing, guardrails, red teaming, hallucination and uncertainty assessment, complex document processing including PDF, DOCX or XML parsing, layout analysis and OCR, Legal Tech, RegTech, or other knowledge-intensive and regulated fields.

• Flexible work in the office or remotely depending on the employee and team;
• Workation within the EU is available;
• Modern centrally located offices and high-quality IT equipment;
• YBrains training program and support for relevant external training;
• Regular feedback;
• Urban Sports Club and EGYM Wellpass memberships;
• Unlimited 1:1 access to OpenUp coaching and mindfulness services;
• Yoga, back training, and running coaching;
• Healthy office snacks and ergonomically equipped workstations;
• Deutschlandticket for commuting to the office;
• JobRad leasing option.