Software Engineer - Infrastructure

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet.

The Team:

The Infrastructure Team builds the foundation that enables enterprise AI to operate reliably at scale. Supporting complex machine learning workloads, massive data processing demands, and hundreds of enterprise customers, our engineers solve challenging problems across cloud infrastructure, distributed systems, scalability, and performance. From optimizing cloud-native architectures to enabling high-performance AI/ML workloads, the team is responsible for creating the resilient, secure, and scalable infrastructure that powers our next generation of enterprise AI capabilities.

The Role:

Design, develop and improve the infrastructure and data-platform capabilities that enable scalable, reliable services. You will work with Python, cloud services, container orchestration, and data processing technologies.

The work you’ll do:

• Design and develop scalable extract, transform, load (ETL) and extract, load, transform (ELT) data integration processes.
• Support agentic infrastructure by provisioning and scaling the compute, model serving, and secure execution environments that AI agents need to run reliably in production.
• Improve and optimize an on-demand predictive modeling platform using Python.
• Use Kubernetes and Docker to orchestrate scalable deployments and manage containers.
• Use contemporary hyperscaler environments  to solve cloud-native engineering problems.
• Improve automated testing, including unit, integration, scale, health-check, and performance tests.
• Support platform security and industry-standard compliance p...

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