AI platform engineer in cloud infrastructure

Join SAP Cloud Infrastructure and help build the next generation of cloud services and platform capabilities powering SAP’s cloud environments. As a Senior AI Platform Engineer, you will design and build scalable cloud-native solutions that solve complex engineering challenges at enterprise scale. Depending on your experience, you may work on cloud services, AI-enabled applications, platform engineering, or European open-source initiatives such as ApeiroRA and NeoNephos. A key initiative in our team is the SCI Agentic AI platform: a multi-agent system progressing from real-time analysis and recommendations to fully autonomous, self-learning cloud operations, reducing MTTR, eliminating toil, and lowering TCO.

• Design, develop, and operate scalable cloud-native applications, services, and APIs using Go, Python, and Kubernetes.
• Drive the agentic AI platform workstream: plan, coordinate, and deliver across engineering teams, aligned to our roadmap (Semantic Data Foundation, Anomaly Detection, Root Cause Analysis, Runbook Automation).
• Architect multi-agent systems integrating LLMs, prediction models, knowledge graphs, and operational data for autonomous infrastructure operations.
• Develop and productionize ML/AI capabilities including anomaly detection, root cause analysis, and runbook automation.
• Drive technical designs and contribute to architecture decisions for strategic cloud and AI initiatives.
• Coordinate cross-functional initiatives, managing dependencies, milestones, and technical documentation.
• Improve software quality through automation, CI/CD, observability, and engineering best practices.

• Several years of experience building and operating production-grade software.
• Strong programming skills in Go (preferred) and/or Python.
• Hands-on experience with Kubernetes and cloud-native architectures (microservices, APIs, distributed systems).
• Solid understanding of software architecture, scalability, reliability, security, and performance.
• Experience with CI/CD, automated testing, DevSecOps, and software engineering best practices.
• Strong understanding of AI and Machine Learning concepts: model training, inference, evaluation, and deployment.
• Experience with or knowledge of agentic AI patterns: multi-agent architectures, tool-use agents, reasoning loops, and agent orchestration.
• Familiarity with LLMs and generative AI: prompt engineering, RAG, fine-tuning, or integrating LLMs into production systems.
• Experience with data science fundamentals: data pipelines, feature engineering, anomaly detection, or predictive modeling.
• Proven ability to lead and coordinate complex technical workstreams across multiple teams.
• Experience translating strategy and roadmaps into actionable delivery plans.
• Comfortable operating in ambiguity: structuring problems, making trade-offs, and driving decisions.
• Comfortable collaborating across teams, cultures, and locations.
• Able to communicate technical topics clearly to engineers, architects, and leadership.
• Structured, reliable, and able to take ownership while working collaboratively.
• Depending on project assignment, candidates may need to be eligible for security clearance under German law.

• Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
• SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best.