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Principal Agentic AI Engineer

SAP
Palo Alto, United Statesfull_timeVerifiedPosted 12 Jun 2026
💰 $299,700/yr($176,300/yr$299,700/yr)

About the role

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed. 

 

This is a hybrid role based out of Palo Alto CA. Hybrid is 3 days a week onsite, 2 days a week remote.

 

Drive AI-enabled innovation and production-ready solutions on SAP Business Techology Platform (BTP)!

 

We are seeking a Principal Agentic AI Engineer to join the BTP Product Management Regional Implementation Group (RIG), a hands-on team that brings the latest SAP technologies to life with early adopter customers across the Americas. 

 

In this role, you will combine deep engineering expertise, AI knowledge, and practical problem-solving skills to implement production-intent using SAP Business AI Platform, specifically Joule Studio 2.0 and related services. You will work closely with customers, product managers, and architects to turn emerging SAP capabilities into real-world applications and help shape the evolution of SAP technologies through actionable product feedback. 

 

If you are energized by solving complex technical challenges, experimenting with cutting-edge AI, and building solutions that make a tangible impact for customers, this role provides a unique opportunity to work at the intersection of innovation, architecture, and implementation excellence. 

 

What you’ll build: 

  • Work with customers across the Americas to architect and deliver production-intent solutions on SAP Business AI Platform, with a focus on AI-enabled scenarios including custom agents, intelligent applications, and intelligent workflows such as n8n. 

  • Partner with your product manager, development architect, and customer teams to deliver high-quality solutions, translating business requirements into scalable architectures, functional designs, and maintainable implementations. 

  • Stay on top of the latest SAP product releases and emerging technologies, evaluating their suitability for customer scenarios, identifying trade-offs, and proposing optimal implementation approaches. 

  • Collaborate on structured product feedback for each engagement, engaging with SAP Product Management and Architecture teams to ensure real-world insights inform product direction. 

  • Contribute to sample implementations, reference architectures, configuration examples, and developer enablement materials, accelerating adoption of new SAP technologies both internally and with customers. 

  • Serve as a technical mentor and subject-matter expert, helping teams apply best practices, experiment safely with new AI approaches, and deliver production-ready solutions with confidence. 

 

What you bring:  

  • University degree in Computer Science, Software Engineering, or related field; 8+ years of software development experience building and shipping production systems. 

  • Strong full-stack engineering fundamentals. You are equally comfortable building frontend experiences, backend services, APIs, and data integrations, and you know how to make them work together in complex customer landscapes.  

  • Proficient in backend languages (Python, Node.js, Java, or Go) and modern frontend frameworks (React, Angular, Vue, or UI5).  Comfortable with Docker, cloud-native development (AWS, Azure, GCP, or SAP BTP), API design, DevOps & CI/CD pipelines. 

  • Practical AI expertise: generative AI, LLM orchestration, prompt engineering, RAG patterns, and agentic architecture. You have moved beyond prototyping and built and maintained AI-powered solutions in production.  

  •  Development experience building agents using modern frameworks and protocols (MCP, A2A, LangGraph, CrewAI, or similar); you have shipped working agents, not just experimented with them.  

  •  Understanding LLM production concerns: grounding, guardrails, latency, cost optimization, and observability. 

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Company

SAP

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