AI Solution Engineer (LLM & Agentic AI)

About the role

Evonik is hiring an AI Solution Engineer focused on LLM and agentic AI. The role covers end-to-end delivery of AI solutions, from understanding business problems with internal customers to building, deploying and maintaining LLM-based applications such as RAG solutions, knowledge assistants, AI agents and tool-using workflows.

Key responsibilities

• Work with internal customers to understand business problems, shape feasible AI options, validate value through prototypes and deliver solutions into productive use.
• Design, build, evaluate and improve LLM-based applications, including RAG, knowledge assistants, AI agents, tool-using workflows and automation flows.
• Own the technical implementation from prototype to production, including application logic, APIs, data pipelines, orchestration, testing, deployment, documentation, monitoring and continuous improvement.
• Build data and knowledge pipelines for AI use cases, with reliable ingestion, preparation, retrieval and access-controlled use of information.
• Connect AI solutions with enterprise systems (e.g. Microsoft, SAP), APIs, knowledge repositories and operational data sources.
• Apply testing, evaluation, responsible AI practices, security, data protection, observability, cost awareness and production support.
• Contribute reusable components, prompts, evaluation approaches, RAG and agent patterns, pipeline templates and implementation guidance.

Required profile

• Several years of hands-on experience in software engineering, AI application engineering, solution delivery, data engineering and/or enterprise integration, with a proven ability to bring solutions into productive use.
• Strong practical experience with LLM-based development, especially RAG, prompt and context engineering, tool use and agentic workflows.
• Ability to work directly with business users, clarify ambiguous needs, translate problems into technical options and communicate trade-offs clearly.
• Good understanding of evaluating and operating AI solutions responsibly, including quality, security, data protection, cost awareness and safe use of agentic workflows.
• Additional experience with enterprise platforms, industrial systems or scientific and technical data environments is valuable.

Required skills

• Solid data integration skills for AI use cases, including structured and unstructured data, APIs and data quality.
• Strong software engineering in Python, with API and backend component development; SQL where needed.
• Experience with Azure or comparable cloud environments, including managed LLM services, retrieval technologies, secure integration and deployment.
• Modern delivery workflows: Git, Azure DevOps or similar, CI/CD basics, containerized deployments, testing and monitoring.

To apply, submit your application online through the company's careers portal, addressing it to the Talent Acquisition Manager and stating your earliest possible start date and salary expectations.