Celonis Lead hands-on implementation of Celonis solutions for financial services customers using AI-augmented workflows. Translate customer needs into technical specifications and ensure measurable impact.
Responsibilities
As a Deployment Engineer, you are the backbone of Celonis delivery. You lead the hands-on implementation of Celonis solutions for enterprise customers, combining platform expertise with AI-augmented workflows to deliver high-quality outcomes, fast. You use Celonis’s AI deployment tools as your primary instruments - directing agents to build data models, generate analyses, and configure operational solutions, while applying your own judgment to validate outputs, adapt to customer context, and ensure business relevance.
This is not a traditional consulting role where you build everything manually. You are an AI-augmented delivery professional: you specify what needs to be built, direct AI agents to execute wherever possible, validate the results, and iterate with the customer. You generate value by understanding the customer’s business, translating their needs into technical specifications and solutions, and ensuring the platform delivers measurable impact.
The Work You’ll Do
Initiate and Connect
Conduct business discovery workshops to translate customers’ strategic objectives into high-impact Celonis use cases
Collaborate with the customer’s IT and business stakeholders to define project scope, data requirements, and success criteria
Ensure data connectivity and extraction pipelines are properly configured, working with specialist resources if required
Direct AI deployment agents (Apollo) to build data models, process analyses, KPIs, and dashboards - writing clear specifications and validating agent outputs against business requirements
Build and configure Celonis solutions across the platform: Process Intelligence Graph, data transformations, process analysis, operational solutions, and AI-powered insights
Identify process inefficiencies and root causes using Celonis technology, always in close collaboration with the customer
Validate AI-generated outputs for accuracy, business relevance, and alignment with customer context - applying domain knowledge where the AI cannot
Lead value creation workshops and define measures to improve process inefficiencies
