Lead Deployment Engineer

The Role

As a Lead 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

Build & Value

• 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
• Define and build KPIs measuring the customer’s success and quantify business impact
• Design and build operational solutions to drive value, adoption and improve process conformance

Rollout, Adoption, and Handover

• Enable key customer users to use and extend the solution independently, setting the foundation for long-term adoption
• Manage project outcomes against timelines, scope, and customer expectations
• Train and demonstrate to customer users, guiding them on the path to sustained value
• Document solution design decisions and configurations for future reference and handoff

Domain & Industry Depth

• Develop and maintain deep expertise in one or more process domains (e.g., Supply Chain, Order to Cash, Procure to Pay, IT Service Management) or industry verticals
• Translate domain knowledge into scalable solution patterns, reference architectures, and best practices that the broader team can leverage
• Proactively identify and standardize high-value use cases within your domain, collaborating with Product and Business Apps teams to shape the platform roadmap

What Makes This Role Different in the AI Era

• You work with AI agents as your primary tools - your job is to direct, validate, and refine their output, not to write every line of code or build every analysis manually
• You need strong specification and context engineering skills - the ability to translate a customer’s ambiguous business need into a precise instruction that an AI agent can execute correctly
• You are expected to continuously learn and adapt as AI capabilities evolve, experimenting with new approaches and sharing what works with your peers
• You balance speed with quality - AI accelerates execution, but you own the judgment calls on whether the output is right for this customer
• You think in sustainable software solutions. While AI agents will generate first results quickly, you need to ensure that the operational solutions you build in Celonis are robust, user friendly, maintainable, and scalable

The Qualifications You Need

• Experience: A minimum of 8+ years in Management or IT consulting, data/solution consulting, or process improvement consulting within software vendors, consulting firms, or system integrators.
• Platform skills: Ability to build and configure solutions on the Celonis platform, including data modeling, process analysis, KPI definition, and automation. Proficiency in PQL, SQL, and Python.
• AI fluency: Comfort working with AI-assisted development tools (e.g., Claude Code, Codex, Cursor, etc.). Ability to write clear specifications, evaluate AI-generated outputs, and iterate effectively. Experience with prompt engineering or context engineering is a strong plus.
• Business and process domain expertise: Strong understanding /deep expertise (based on seniority level) of enterprise business processes and financial metrics. Knowledge of standard ERPs (SAP, Oracle) and process areas (Inventory Management, Order to Cash, Procure to Pay, Accounts Payable) is a strong plus.
• Consulting skills: Ability to steer customer workshops, present findings to management, manage stakeholder expectations, and deliver outcomes in the face of adversity and ambiguity. Comfortable working with both technical and business audiences.
• Analytical mindset: Excellent problem-solving skills with a value-driven orientation. Ability to translate business requirements into technical solutions and quantify business impact.
• Learning agility: Willingness to continuously develop expertise through experimentation. Comfort with ambiguity and evolving tools.
• Education: Bachelor’s or Master’s in Technology Management, Business Informatics, Computer Science, Engineering, Business Administration, or a comparable field.
• Languages: Fluency in English required. Additional languages are a plus.
• Travel: Willingness to travel to customer location up to 50%, according to customer requirement and project delivery phases.