SAP is looking to architect, scale, and harden its next generation of generative AI services to accelerate the path from idea to outcome, delivering business value across all SAP lines of business.
Requirements
- Deep proficiency in Python and familiarity with Go/TypeScript; experience with distributed systems and orchestration frameworks.
- Strong background in ML/AI, including large language models, embeddings, RAG, and/or multimodal generation.
- Hands-on experience with cloud-native infrastructure (Kubernetes, AWS/Azure) and modern data stores (Postgres, Cassandra, vector DBs).
- Proven track record of delivering production AI systems at scale.
- Strong problem-solving skills and ability to balance innovation with enterprise-grade reliability.
- Experience mentoring engineers and shaping engineering culture.
Responsibilities
- Architect and optimize ML-driven workflows for multi-agent orchestration (LangGraph) across DRP, Experience Builder, and Visual Services.
- Lead technical design discussions, mentor junior engineers, and set engineering standards for reliability and scale.
- Evaluate, fine-tune, and integrate foundation models (text, multimodal, diffusion) through SAP’s GenAI Hub and third-party providers (e.g., Amazon Bedrock).
- Design evaluation frameworks and dashboards for quality, safety, and enterprise trust in generative outputs.
- Partner with product teams to define roadmaps and deliver features that serve Sales, Marketing, Finance, HR, and beyond.
- Collaborate with cross-functional SAP AI teams on shared infrastructure, governance, and interoperability.
- Stay at the forefront of ML/AI trends and bring best practices into the team’s architecture and execution.
Other
- 6+ years of professional experience in machine learning engineering, software engineering, or applied research roles.
- Experience mentoring engineers and shaping engineering culture.
- Expected Travel: 0 - 10%
