Senior Backend Engineer

Global Cloud Infrastructure & Delivery (GCID) develops and delivers services for cloud infrastructure and cloud operations to SAP Lines of Business (LoB) and through them, our external customers. We support LoBs and their customers' cloud adoption journey through four hyperscaler public clouds and SAP's Infrastructure-as-a-Service. 

Cloud Observability (CO) is the foundation for cloud operations. It delivers critical capabilities for infrastructure and application operation, security management by providing a fully integrated end-to-end observability product across our different Line of Business.  

 
About the Role: 

We are looking for a Senior Backend Engineer with strong development fundamentals and production experience building and operating backend services in cloud environments. This role is ideal for an engineer who has led or owned Python-based applications, is comfortable with DevOps and CI/CD practices, and is interested in growing into AI and agent-based systems over time. 
 

You will join a global, multidisciplinary engineering team responsible for developing and operating cloud observability services used across SAP’s global infrastructure. While AI and automation are part of our roadmap, this role does not require deep AI expertise on day one. Instead, we are looking for strong engineers who are curious, adaptable, and motivated to upskill in AI-related technologies as part of their growth. 

What You’ll Do: 

• Design, develop, and operate backend services primarily in Python, supporting observability platforms for cloud infrastructure and applications. 

• Build and maintain REST APIs using frameworks such as FastAPI or Flask. 

• Own services end to end, including development, deployment, monitoring, and operational support. 

• Contribute to CI/CD pipelines, automated testing, and release processes to ensure reliable and repeatable deployments. 

• Work with containerized workloads using Docker and Kubernetes in public cloud environments (AWS, Azure, GCP). 

• Analyze operational data such as metrics, logs, and alerts to improve service reliability and reduce operational noise. 

• Collaborate closely with engineers and product managers in an Agile (Scrum) environment. 

• Participate in a global on-call rotation following a “follow-the-sun” model.  

• Gradually contribute to and learn about AI-driven and agent-based capabilities used to improve observability and operational efficiency. 

What You Bring: 

Core Engineering Experience 

• 5+ years of professional software development experience, with a strong focus on backend systems. 

• Proven experience building and maintaining Python-based applications in production environments. 

• Solid understanding of RESTful API design and backend frameworks (FastAPI, Flask, or similar). 

• Experience working in cloud-native environments, including Docker, Kubernetes, and at least one major cloud provider (AWS, Azure, or GCP). 

• Strong grasp of CI/CD concepts and pipelines, including version control (GitHub), configuration formats (JSON, YAML), and automated testing. 

• Familiarity with monitoring, logging, and performance management tools. 

AI Interest  

• Basic knowledge or personal exposure to AI/ML or Generative AI concepts, or a strong interest in learning. 

• Curiosity about how AI and automation can be applied to observability, operations, and incident reduction. 

• Willingness to upskill in areas such as agent-based systems, ML-assisted analytics, or LLM-driven tooling as part of the role. 

Professional Skills 

• Strong analytical and problem-solving mindset. 

• Ability to work independently while collaborating effectively within a global team. 

• Clear written and verbal communication skills in English. 

• Self-driven, pragmatic, and comfortable working in complex production environments. 

Education: 

• Bachelor’s degree or equivalent experience in Computer Science, Software Engineering, or related field. 

Nice to Have: 

• Experience with observability tools such as Elasticsearch, Splunk, or similar. 

• Exposure to infrastructure-as-code or automation tools (Terraform, Helm, Ansible). 

• Familiarity with large-scale cloud or enterprise infrastructure environments.