AI Agentic Engineering Specialist - Corporate Processes & Information Technology

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 SAP Vancouver office, working in-office with the team 3 days per week. **

What you'll do

We are looking for a AI Engineering Specialist who can design, build and bring to production, enterprise-grade AI solutions across processes in Go-to-Market operations. You will play a key role in developing scalable (gen) AI and multi-agent systems and products that drive measurable business impact. The ideal candidate combines strong software engineering skills, deep understanding of data and MLOps practices, and hands-on experience with modern AI frameworks. 

In this role, you will work closely with AI Product Owners, data scientists, and architects to translate AI concepts into reliable, production-ready systems. You’ll design and implement AI solutions, setup and develop big data pipelines and ensure high standards of scalability, observability and compliance. You’ll thrive in an agile, collaborative environment that values continuous learning, engineering excellence and innovation, helping shape the next generation of enterprise AI solutions at SAP. 

Responsibilities

• Design, develop and deploy AI and (gen)
  AI services and solutions from proof of concept to full enterprise production 
• Build and maintain data pipelines and model deployment workflows for scalable, secure AI systems 
• Implement CI/CD and MLOps practices to automate model training, testing and deployment 
• Collaborate with Product Owners and data scientists to translate requirements into technical specifications 
• Develop and integrate multi-agent AI and LLM-based products and solutions 
• Ensure reliability, observability and compliance of deployed AI solutions 

What you bring

• Degree in computer science or a similar field 
• 3 to 6 years of software development experience
• Advanced Coding skills in Python (preferred) or Java, with solid understanding of software engineering principles 
• Experience with backend frameworks (FastAPI, Flask, Django) and microservice architectures 
• Familiarity with containerization and orchestration tools (Docker, Kubernetes, Git Hub Actions, MLFlow) 
• Familiarityimplementing CI/CD and MLOps pipelines in cloud environments (Azure ML, Databricks, AWS) 
• Hands-on experience with data ETL, APIs and model deployment workflows 
• Knowledge of distributed systems and data platforms for big data  
• Fluent English and a proactive, problem solving mindset 

Nice to have but not a must

• Experience with multi-agent or generative AI frameworks (e.g., Lang Chain, CrewAI) 
• Familiarity with SAP AI Core, SAP BTP 
• Experience with agile frameworks (e.g., Scrum, SAFe) and project management tools (e.g., Jira) 
• Understanding of Agile, SAFe methodologies and collaborative engineering practices 

These skills are a plus. If you don’t have experience in all these areas, we’ll provide the resources and training you need to become a leader in cutting-edge AI technologies. 

Meet your team

Join the multi-disciplinary CE3 (Cross Engineering, Experience & Excellence) unit within Channels & Cross Engineering in Corporate Processes & Information Technology (CPIT). We partner across CPIT to design and deliver enterprise-grade Agentic AI autonomous, goal-oriented agents that interpret intent, orchestrate multi-step workflows, and deliver outcomes with minimal human intervention.

We’re building a unified Agentic AI platform with reusable capabilities—contextual reasoning engines, safe-action frameworks, enterprise guardrails, and robust integration patterns—while emphasizing rapid experimentation, cross-team enablement, and ethical governance. Backed by SAP’s trusted data and domain expertise, our work accelerates automation, personalization, and…