Description:
We are looking for an Agenting AI Engineering Expert who can design, build and bring to production, enterprise-grade AI solutions across processes in our operations. You will play a key role in developing scalable (gen) AI and multi-agent systems and products that drive measurable business impact. The ideal candidate combines strong software engineering skills, deep understanding of data and MLOps practices, and hands-on experience with modern AI frameworks.
In this role, you will work closely with AI Product Owners, data scientists, and architects to translate AI concepts into reliable, production-ready systems. You’ll design and implement AI solutions, setup and develop big data pipelines and ensure high standards of scalability, observability and compliance. You’ll thrive in an agile, collaborative environment that values continuous learning, engineering excellence and innovation, helping shape the next generation of enterprise AI solutions at SAP.
Responsibilities
- Design, develop and deploy AI and (gen)AI services and solutions from proof of concept to full enterprise production
- Build and maintain data pipelines and model deployment workflows for scalable, secure AI systems
- Implement CI/CD and MLOps practices to automate model training, testing and deployment
- Collaborate with Product Owners and data scientists to translate requirements into technical specifications
- Develop and integrate multi-agent AI and LLM-based products and solutions
- Ensure reliability, observability and compliance of deployed AI solutions
- Guide and mentor junior colleagues to foster AI engineering excellence across teams
What You Bring
- Bachelor degree in computer science or a similar field
- At least 10+ years experience in software development
- Advanced coding skills in Python (preferred) or Java or node.js, with solid understanding of software engineering principles
- Experience in designing and architecting enterprise software solutions
- Experience with backend frameworks (FastAPI, Flask, Django) and microservice architectures
- Familiarity with containerization and orchestration tools (Docker, Kubernetes, GitHub Actions, MLFlow)
- Experience implementing CI/CD and MLOps pipelines in cloud environments (Azure ML, Databricks, AWS)
- Hands-on experience with data ETL, APIs and model deployment workflows
- Knowledge of distributed systems and data platforms for big data
- Understanding of Agile, SAFe methodologies and collaborative engineering practices
- Fluent English and a proactive, problem solving mindset
- Nice to have but not a must:
- Experience with multi-agent or generative AI frameworks (e.g., LangChain, CrewAI)
- Familiarity with SAP AI Core, SAP BTP
- Experience with agile frameworks (e.g., Scrum, SAFe) and project management tools (e.g., Jira)