Application ai developer állás, munka

• Design, implement, and maintain high-performance, scalable backend services that power our platform.
• Work on resilient distributed systems using Kafka for event-driven workflows and Redis for real-time, fast data access and caching.

We are looking for an Expert DevOps Engineer (f/m/d) within the Sovereign Cloud Delivery & Operations team in the Customer Services & Delivery board area, focused on the Sovereign Cloud deployment of SAP SuccessFactors (HCM). In this role, you will join the Multi-Tenant Engineering team: We own,...

• Design our software, analyze problems and implement your solutions independently focusing on C++ development and network protocols
• Develop complex software modules together with our agile development teams

• You will take a key role in developing our secure edge platform for real-time data processing applications.
• You will design, implement, and evolve robust, and observable platform components, APIs and SDKs for developing, deploying, and operating real-time applications.

• Design, develop, and implement platform solutions that enhance the reliability, security, and scalability of the AI Platform infrastructure.
• Provide technical leadership in cloud infrastructure, networking, CI/CD, and security for AI and MLOps workloads.

• Design, develop, and maintain applications.
• Optimize and enhance existing applications and infrastructure.
• Ability/interest to work with machine learning.
• Collaborate and communicate with various teams within the company.
• Ensure all applications reflect our internal policies and standards.

• verify mixed-signal designs on block and system level resting upon formal and functional verification
• interpret product requirements to create the verification concept and the product verification specification
• perform random-constraint testbenches according to the state of the art

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Support the data engineering team in reconciling data between the new and the legacy systems
• Participate in monitoring, troubleshooting, and resolving data processing issues

• Implementation of software solutions for research purposes
• Translation of research code into robust software (e. g., optimization, refactoring)
• Contribution to research projects to allow deployment (containerization, virtualization)