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Celonis

Process intelligence platform for end-to-end efficiency

Software Engineer

Backend EngineeringPosted on Nov 10
Full-time

About the Job

Requirements

  • At least 3 years of industry experience building distributed systems, cloud-based API services, or enterprise cloud data platforms.
  • Strong computer science fundamentals and proficiency in Python.
  • Experience developing reliable, enterprise-grade software or services.
  • Experience with SQL and databases such as PostgreSQL, DynamoDB, or Amazon RDS.
  • Ability to collaborate in a team and mentor engineers through the software development lifecycle.
  • Familiarity with data warehouse or data lake architecture and large-scale data processing.

Responsibilities

  • Design and develop product features aligned with the product and engineering roadmap.
  • Build platform capabilities that enable AI agentic workflows, including tool-calling APIs, workflow orchestration, and production observability and guardrails for agents.
  • Scale APIs and workflows using principles of scalable and robust distributed systems.
  • Design for fault tolerance, high availability, performance, and scalability.
  • Ensure platform services are operationally ready and meet customer service-level commitments.
  • Collaborate with teammates and contribute to code reviews and knowledge sharing.

Desired Qualifications

  • Experience with distributed computing frameworks for machine learning workloads; familiarity with Ray is a plus.

About the Company

Celonis

Process intelligence platform for end-to-end efficiency

Celonis builds a Process Intelligence platform that creates a digital twin of an organization's end-to-end processes by collecting data from multiple systems to map how work actually flows. Users from different departments can see bottlenecks, inefficiencies, and improvement opportunities in a system-agnostic view, enabling cross-functional collaboration. Its business model charges customers for platform usage and aims to help organizations accelerate digital transformation and achieve cost savings. Its goal is to help organizations streamline operations and realize measurable efficiency gains through data-driven process improvements.

Company size
1,001-5,000
Company stage
Series D
Total funding
$2.4B
Headquarters
Munich, Germany
Founded
2011

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