Architectural design and ownership of a platform for hosting and operating a multitude GenAI use cases
End-to-end design and implementation of scalable, resilient, and secure services (microservices developed in Python, serverless, APIs, event-driven architectures) by using the best software design patterns and code guidelines
Selection, integration, and orchestration of GenAI components, including knowledge management, prompt/pipeline management, agentic workflows and tooling for efficient MLOps/AIOps practices.
Definition and establishment of engineering best practices covering data engineering, reusable service design, CI/CD for automated deployment and monitoring.
Close collaboration with global stakeholders, product owners, feature teams, and internal/external development partners to ensure seamless platform evolution.
Mentoring and technical leadership for engineering teams, guiding architectural decisions and contributing to mid and longterm roadmap planning.
Operational responsibility for running platform components in production, ensuring stability, security, compliance, and reliability.
What Should You Bring Along
Bachelor's Degree in Computer Science, Engineering, Artificial Intelligence, or a related field
Minimum of 5-7 years of experience on a similar position
Successfully completed studies in computer science, informatics, or a comparable technical field
Several years of experience in technical leadership, guiding engineers and/or feature teams, paired with strong enterprise-wide strategic and operational awareness
At least two years of hands-on experience operating a production-grade platform in an enterprise context, including reliability, scaling, observability, and lifecycle management