Company Description

Job Description

What you'll bring

You are an applied AI scientist with solid software engineering skills and a proven track record in production AI systems. You bring strong communication skills, a collaborative approach, and the creative thinking and learning agility to adapt as the role evolves.

• A degree in Computer Science, AI, Machine Learning, Data Science, Statistics, or a related field, or equivalent practical experience; a master's degree or PhD is an advantage.
• Strong Python skills and the ability to write production-quality code; experience building APIs, reusable libraries, automated pipelines, and cloud-deployed components, including CI/CD and automated testing.
• Foundations in applied statistics, machine learning, deep learning, NLP, and information retrieval, with practical experience in LLM applications, RAG, embeddings, semantic retrieval, and agentic workflows.
• Experience designing evaluation datasets, benchmarks, and quality metrics, with understanding of offline and online evaluation, statistical significance, and the ability to trace AI system failures to their root cause.
• You take a useful and accountable approach to AI. You use AI-assisted tools and automation to create better solutions. You also make sure that AI-generated outputs are high quality, safe, and aligned with our goals.
• Fluency in English is required for this role.

What you'll build

You will lead the scientific methodology and evaluation standards for generative AI, RAG, and agentic systems - from hypothesis and experiment through to production.

• Own the scientific methodology, evaluation strategy, and quality standards for generative AI, RAG, and agentic systems - defining hypotheses, baselines, success metrics, and acceptance criteria.
• Develop benchmarks and evaluation methods covering retrieval quality, grounding, factual consistency, safety, and task completion - backed by responsible, privacy-aware datasets.
• Perform systematic error analysis to trace failures to their root - whether in data, retrieval, ranking, context, prompts, models, tools, or agent orchestration.
• Research and evaluate embeddings and hybrid search. Focus on reranking, model selection, and agent architectures. Use controlled experiments. Perform both offline and online evaluations. Apply validated LLM-as-a-judge methods.
• Design, implement, and operate production-grade AI capabilities, evaluation services, and data pipelines - with monitoring for quality, drift, latency, and cost.
• Work with product managers, domain experts, and engineers. Apply validated approaches in production. Share scientific and engineering practices across SAP Globalization. Mentor technical colleagues.

Where you belong

You'll join SAPGLO E-Invoicing Localization, part of SAP Globalization AI - a global team across 40 locations building AI agents, intelligent tools, and the infrastructure to scale them. The focus is on applying AI to coding, research, automation, and software design to accelerate compliant solutions for markets worldwide. Learning, coaching, and knowledge sharing are part of how the team runs. This is an active build phase - a good moment to shape how AI is adopted in enterprise localization at SAP.

Equal Employment Opportunity (EEO) Statement

Our company does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

Qualifications

Additional Information

About SAP
With a global network of customers, partners, employees, and thought leaders, SAP helps the world run better and improves people’s lives.
As a leader in enterprise applications and business AI, SAP stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience.

We win with inclusion

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. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or complete your application, please send an email with your request to the Recruiting Operations Team: Careers@sap.com.

For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

Qualified applicants will receive consideration for employment without regard to age, race, religion, national origin, ethnicity, gender (including pregnancy and childbirth), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

Successful candidates might be required to undergo a background verification with an external vendor.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.