The Platform & System Operations (PSO) organization within the Global Cloud Services (GCS) group operates shared IaaS platforms in SAP data centers (DCs) and delivers SAP systems on top of the IaaS platforms (private or public cloud). We adapt, innovate and simplify to achieve “stability, speed and scalability” in order to achieve SAP's business objectives. We:
- Operate Compute/Storage stacks of the shared IaaS platforms in SAP DCs.
- Deliver and operate SAP Product Development, Demo, Training, Consulting & Support systems.
- Ensure maximum uptime and OLA adherence by applying DevOps and ITSM principles.
- Drive continuous improvement towards integrated and intelligent automated operations.
The AIOps team uses AI and big data to aggregate observational data (from monitoring systems output, job logs, syslogs, etc.) and engagement data (from ticketing, incident, and event recording system data) to produce a virtuous circle of continuous insights yielding continuous improvements and fixes.
As an Associate AIOps Engineer, you will work with a team of experienced researchers, data scientists, application developers and cloud operations experts to take on evolving challenges in the field of AIOps. You will have the chance to work with the rich data sets on real-world problems. Your primary goal will be to implement state-of-the-art algorithms and to develop new approaches and technologies for deriving value from available data.
You will have a chance to select and implement the best technologies and approaches based on your own experience, judgment, and experimentation results. This role combines (1) experience with machine learning and deep learning (2) practical knowledge of working with scalable platforms for processing of huge data sets (3) ability to understand the data, associated processes and business implications, (4) scaling from minimum viable product up to shippable code, and (5) build and maintaining innovative new solutions from the ground-up.
Expectations & Tasks
- Explore, understand, and implement most recent Machine Learning algorithms and approaches for supervised and unsupervised machine learning and deep learning.
- Handle and process multi-terabyte data sets in scale-up and scale-out environments.
- Engage in full stack development from REST service to persistence adopting latest state-of-the-art technologies.
- Ability to design, develop and debug cloud applications. Ideally have some experience developing application on modern cloud platform.
- Create excellence both in terms of results, quality and system scalability through continuous evaluation, analysis, and refinement of the application implementation.
- Use AI and big data to identify opportunities and work with partner teams to improve systems availability and automate/optimize operations.
- Develop business cases for automation and partner with the relevant teams to implement them.
THE ROLE REQUIREMENTS
- Bachelor’s or master’s degree in computer science or related field.
- Solid foundation in computer science, with strong competencies in algorithms, data structures, design patterns, and software design principles.
- Proficiency in at least one server-side programming language such as Java, Scala, Python, C#, C++
- Experience with distributed version control (e.g. Git or GitHub).
- Possess knowledge in:
- Application of Machine Learning/Artificial Intelligence in IT operations.
- Big data, data analytics theory and application.
- Software engineering principles (preferably Agile/Scrum) and their application to the creation of self-healing infrastructure and applications.
- Cloud infrastructure operations and automation technologies.
- Widely used automation tools/technologies in the infrastructure environment.
- ITIL Service Management Framework.
- Application architecture and monitoring technologies.
- Able to keep abreast of emerging technologies, methods and best practices.
- Excellent communication (written, verbal and presentation) and interpersonal skills.
- Self-motivated, decisive, with the ability to adapt to change and competing demands.