Lead AI Engineer - hybrid (m/f/d)

Trust something new, grow beyond itself and redefine the boundaries of the feasible. That is exactly what our employees can and should live daily. To set the pace with our innovations and make it great. Because there are a lot of fascinating people behind every successful company. ZEISS employees work in an open and modern environment with numerous development and further training opportunities. Our culture is characterized by expert knowledge and team spirit. All this is supported by the special ownership structure and the long-term goal of the Carl-Zeiss Foundation: to advance science and society together.

Today dare. Inspire tomorrow.

Diversity is part of ZEISS. We look forward to your application regardless of gender, nationality, ethnic and social origin, religion, world view, disability, age as well as sexual orientation and identity.

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As an AI engineer, you play a central role in the development and integration of innovative AI solutions into existing software systems. Their focus is on the rapid prototyping and use of existing AI models and frameworks to develop agent-based applications and generative AI solutions. You work closely with interdisciplinary teams to contribute AI innovations to the organization and demonstrate their potentials. In doing so, you act as an important interface to key business areas such as Enterprise Architecture Management and IT Security to ensure that all solutions meet the highest standards.

Conception and prototyping: selection and integration of AI frameworks, models and platforms that meet the requirements of the organization

Development of agent-based AI prototypes (Agentic AI) using cloud and on-premise APIs

Cooperation with disciplines to understand requirements and translate them into technical concepts

Advice and enablement: support for teams in the introduction of AI technologies, including the creation of roadmaps and action recommendations

Implementation of workshops, training and training to promote acceptance and understanding of AI technologies

Building an internal AI community to strengthen knowledge sharing and cooperation

Collaboration with key stakeholders: Close coordination with Enterprise Architecture Management to ensure that AI solutions can be integrated into the comprehensive corporate architecture

Cooperation with IT Security to take account of data protection and security requirements at an early stage and secure all solutions accordingly

Support in handing over successful prototypes to IT and development teams for further development and scaling

Trend observation and innovation: Active engagement with current trends and developments in the field of AI (Trend Radar)

Identification of new technologies and approaches that could be relevant to ZEISS and evaluation of their potential for the organisation

Measurable results: documentation and communication of the results of pilot projects using KPIs such as time savings, process improvements and innovation potential

Education: University degree in computer science, engineering or a comparable discipline

Professional experience: At least 5 years relevant professional experience in the development and integration of software solutions, of which at least 2 years experience with modern AI systems (e.g. Generative AI, LLMs, Agentic AI)

Experience in fast prototyping and building agent-based AI applications

Detectable ability to evaluate AI technologies in an entrepreneurial context and demonstrate their potentials

Technological competencies: knowledge of Python for AI development and understanding of .NET/C# interfaces for system integration

Experience with agentic frameworks and orchestration tools such as LangChain (LangGraph), Microsoft Semantic Kernel or AutoGen

Competence in handling LLMs, both cloud-based (e.g. Azure OpenAI) and on-premise/local (e.g. by vLLM, Ollama, Hugging Face)

practical experience with RAG architectures (Retrieval Augmented Generation) and vector databases (e.g. Qdrant, Azure AI Search)

Confidence with API development (e.g. FastAPI) and containerization (Docker) to provide functional prototypes

Personal skills: ability to develop complex technical concepts in a comprehensible way for different target groups

Enthusiasm for AI and the ability to inspire others for these technologies

strong ability to collaborate with different stakeholders, in particular Enterprise Architecture Management and IT Security

Flexibility and pragmatism to develop innovative solutions quickly and efficiently