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 practices.

The qualifications you need

2–4 years of software engineering experience and a bachelor’s or master’s degree in computer science or engineering.
Advanced experience with Python, AWS/Azure/OCI/GCP services, and/or ETL/ELT pipelines.
Understanding of software design patterns and testing best practices.
Experience with Kubernetes, Amazon EKS, or Azure AKS is a plus.
Knowledge of streaming data processing and real-time analytics.
Familiarity with data governance, security, and compliance best practices.

Visa sponsorship is not offered for this role.

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.

The base salary range below is for the role in Massachusetts, based on a Full Time Schedule.

$134,000—$158,000 USD

What Celonis can offer you

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.