Senior AI Observability Engineer
hace 7 días
About SAP
SAP is a leading provider of enterprise software solutions, helping over 400,000 customers worldwide to work more efficiently and effectively. With a strong presence in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management.
Our Mission
We are a cloud company with 200 million users and over 100,000 employees worldwide, driven by a purpose to help our customers succeed. Our highly collaborative team ethic and commitment to personal development enable us to deliver innovative solutions that meet the needs of our customers.
About the Role
We are seeking a Senior AI Observability Engineer to join our Global Cloud Infrastructure & Delivery (GCID) organization. As a key member of our Service Reliability Engineering (SRE) team, you will contribute to the development of AI solutions that power our observability services, using machine learning and large language models to enhance reliability and availability.
Key Responsibilities
- Collaborate with engineering and product management teams to develop and implement AI-powered observability solutions.
- Design and develop deep learning and NLP models to enhance alert management, metric analysis, and log processing.
- Support troubleshooting during major incidents related to our global cloud infrastructure, ensuring excellence in triage and resolution.
- Contribute to the development of data analysis and generation tools to support AI research and development projects.
- Train and fine-tune AI models to improve their accuracy and performance.
Requirements
- 4+ years of experience in professional or enterprise development, with strong knowledge of Python and JavaScript programming languages.
- Proven experience in REST API implementation using Flask or FastAPI, and microservice-based development.
- Understanding of CI/CD pipelines using Azure, Jenkins, Travis, or similar, and hands-on experience with docker containers and Kubernetes.
- Experience with public cloud environments such as GCP, AWS, or Azure, and solid understanding of JSON, YAML, and GitHub.
- Strong familiarity with Enterprise-class Fault Monitoring and Performance Management tools.
- Experience with ML frameworks like PyTorch, TensorFlow, or similar, and knowledge in Prompt Engineering, Large Language Models, RAG, and Embeddings.
Preferred Qualifications
- Knowledge Graphs, Graph DB's, and Graph Theory.
- Experience with Elasticsearch, Splunk, or similar.
- Experience in web development frameworks.
- Familiarity with Terraform, HelmChart, Ansible, or similar tools.
- Knowledge about Kubeflow, MLFlow, Dataflow, or similar technologies.
What We Offer
We offer a dynamic and collaborative work environment, with opportunities for professional growth and development. Our team is passionate about delivering innovative solutions that meet the needs of our customers, and we are committed to helping our employees succeed.
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