AI Developer

About the Role

We are seeking a seasoned AI Developer specializing in generative AI technologies to build and deploy a production-grade AI assistant tailored for railway passengers. This role involves developing both frontend and backend elements and leveraging cutting-edge large language model (LLM)-based applications, as well as advanced agentic and context engineering techniques within an international setting.

Key Responsibilities

• Create and maintain an AI assistant designed to assist railway users in a production environment.
• Develop frontend and backend components of the AI solution, ensuring seamless integration.
• Design and implement innovative AI solutions based on LLMs, agentic engineering methodologies, and Tool-Calling Loop architectures.
• Work extensively with Context & Harness engineering, Retrieval-Augmented Generation (RAG), and MCP server frameworks.
• Integrate various enterprise AI platforms and heterogeneous data sources.
• Collaborate closely with multinational project teams, executives, and stakeholders to meet project objectives.

Required Qualifications and Experience

• At least three years of professional experience developing production LLM-based applications.
• Over three years of hands-on experience with agentic engineering practices.
• Minimum one year working with Tool-Calling Loop systems.
• More than one year combining large language models with deterministic software components as well as proficiency in Context & Harness engineering.
• Demonstrated ability to communicate effectively with project teams, decision-makers, and stakeholders.
• Possession of at least two relevant reference projects evidencing expertise.
• Language proficiency at German A2 level and English B2 level or higher.

Preferred Skills and Additional Expertise

• Experience developing AI solutions considering governance, security, and compliance standards.
• Knowledge of observability practices including monitoring, tracing, and evaluating AI systems.
• Familiarity with enterprise AI platforms featuring AI gateways, prompt management, and model governance.
• Proficiency in multi-agent architectures and orchestration techniques.
• Hands-on experience with Retrieval-Augmented Generation (RAG) and integrating diverse data sources.
• Expertise in designing and operating MCP servers.