Senior AI/ML Engineer, Agentic Workflows
We are looking for a Senior AI/ML Engineer to join the Enterprise AI Center of Excellence (EAI CoE), driving value creation through best-in-class Big Data, AI and Search platforms, solutions and services. Within the EAI CoE, the AI Factory accelerates the implementation and scaling of impactful AI use cases, empowering both professional and citizen data scientists through standardized frameworks and automation. In this role, you will design, develop and deploy AI-powered solutions that automate and optimize incentive management or controlling processes, building intelligent agents that analyze financial and operational data, validate business rules, identify anomalies and optimization opportunities and support planning, forecasting and decision-making through automated workflows and actionable insights.
Responsibilities
- Design and develop AI-powered solutions to automate and optimize incentive management or controlling processes
- Build intelligent agents to analyze financial and operational data and validate business rules
- Identify anomalies and optimization opportunities within business processes
- Support planning, forecasting and decision-making through automated workflows and actionable insights
- Implement CI/CD and MLOps pipelines across cloud environments
- Deploy and maintain models using containerization and orchestration tools
- Collaborate with cross-functional teams following Agile and SAFe methodologies
- Apply software engineering principles to build scalable and maintainable AI solutions
- Manage data ETL processes, APIs and model deployment workflows
Requirements
- 3+ years of experience with multi-agent or generative AI frameworks such as LangChain or CrewAI
- Advanced coding skills in Python (preferred) or Java with a solid understanding of software engineering principles
- Experience with backend frameworks such as FastAPI, Flask or Django and microservice architectures
- Familiarity with containerization and orchestration tools such as Docker, Kubernetes, GitHub Actions or MLFlow
- Experience implementing CI/CD and MLOps pipelines in cloud environments such as Azure ML, Databricks or 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 and SAFe methodologies and collaborative engineering practices
- Fluent English and a proactive problem-solving mindset
Nice to have
- Knowledge of ML/AI methodology and AI architectures
- Background in Data Science
- Familiarity with SAP AI Core and SAP BTP
- Experience with agile frameworks such as Scrum or SAFe and project management tools such as Jira
