AI Engineer (Developer) - Autonomous Compliance Foundation

What you'll bring

You have robust coding and debugging skills and a solid foundation in building cloud-based microservices (Java, Node.js, Python, or similar) — through your studies, internships, or personal projects. You understand APIs, REST, distributed-systems basics, and CI/CD practices.

You've worked with AI/LLM tools — prompt design, basic RAG patterns, and calling AI services from an application — and, above all, you have an instinct to automate and explain: to turn AI output into something a non-technical user can act on.

You're curious about how systems behave in production — observability, performance, monitoring — and you bring an ownership mindset and good testing, validation, and troubleshooting habits.

Nice to have (not required): a couple of years of professional experience is welcome — for example building and operating cloud-based microservices in production, integrating LLMs into live applications, or working with observability and performance tuning. Familiarity with e-invoicing or EDI document formats (XML, JSON, Peppol BIS), or the ability to ramp up fast on domain-specific formats, is also a plus.

What you'll build

You'll join the Autonomous Compliance Foundation team. The main focus is autonomous compliance: turning new regulatory and legal requirements into working, compliant software — from legal text to running code — through an automated pipeline with human validation gates that reduces the manual effort of implementing legal changes. The pipeline also produces the downstream deliverables: documentation (implementation notes and SAP Help), training, and rollout materials. E-invoicing is the first focus area.

The specifications and curated knowledge this pipeline produces also ground SAP Business AI agents, so they can reason about and act on compliance topics precisely and stay current as regulations change.

• Help design, develop, and maintain production-grade AI-enabled features and services across the pipeline, with a focus on scalability and reliability.
• Contribute to the human-validation gates that keep legal and compliance experts in control of what the pipeline produces.
• Help produce and curate the grounded knowledge that SAP Business AI agents rely on, so their compliance answers and actions stay reliable and traceable to source.
• Build self-service and AI-assisted flows that let customers configure e-invoicing solutions without engineering intervention — guided setup wizards, mapping explainers, implementation-assistant tools — and the infrastructure that powers them. This is about designing the interaction layer that makes AI outputs actionable for non-technical users, not just consuming AI APIs.
• Help extend the pipeline beyond code to generate documentation, training, and rollout assets from the same specifications.
• Build and improve evaluation and benchmarking pipelines to measure AI output quality and system performance.
• Help monitor and improve application health, latency, throughput, and efficiency; debug production issues and contribute to incident analysis and stability fixes.
• Support and enhance CI/CD pipelines and deployment workflows, and collaborate cross-functionally to refine requirements and improve system design.

In the longer horizon, the team moves localization from code-based to configuration-based: legislation expressed as structured configuration rather than code, new localizations onboarded against a common platform, and compliance behavior that agents can extend and adapt — with a human always in the loop.

Where you belong

You'll take growing ownership of features and modules as you develop, working closely with product, platform, AI, and consulting teams to align on goals and deliver quality results. The team values direct communication, shared accountability, and continuous improvement. You'll take part in code reviews, learn from skilled engineers, and build your expertise in AI-native application development.

Skills used in this role

AI adoption capability, AI output quality assurance, AI-assisted development, context engineering, agentic orchestration, agentic engineering, application security, cloud architecture, observability, semantic retrieval, high-availability engineering, troubleshooting, evaluations and benchmarking engineering, CI/CD.

Equal Employment Opportunity (EEO) Statement

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About SAP
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