About the Role
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.
Responsibilities
•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.
Requirements
•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.
Benefits
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.
