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Celonis

Process intelligence platform for end-to-end efficiency

Applied Value Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeAmsterdam, Netherlands

About the Job

Requirements

  • Demonstrated experience supporting executive-facing presales and value engineering, including technical close, AI transformation narratives, accountable proof-of-value execution, return-on-investment and total-cost-of-ownership modeling, and pitching visionary solutions.
  • Solid knowledge of core business processes and industry landscapes, such as supply chain or finance, and ability to connect operational bottlenecks to strategic AI solutions for business leaders.
  • Proficiency in Python, API design, SQL, data integration, and machine learning and AI libraries including PyTorch, TensorFlow, scikit-learn, XGBoost, and Hugging Face Transformers.
  • Hands-on experience with agentic AI systems, including large language model orchestration, tool use or function calling, retrieval-augmented generation, agents, prompt engineering, or agentic patterns for enterprise workflows.
  • Experience with model deployment, monitoring, machine learning operations or large language model operations, and lifecycle management across cloud services such as AWS Bedrock, Azure AI, and GCP Vertex AI.
  • Understanding of cloud reference architectures, identity and access, data governance, privacy, and compliance.
  • Strong presentation skills for internal and external stakeholders, including executives, in whiteboarding sessions, formal readouts, and demos.
  • Fluent English and exceptional executive presence.
  • Equivalent work experience may be accepted in place of the preferred degree.

Responsibilities

  • Diagnose strategic and key operational challenges for strategic global accounts to discover and build tailored, domain-specific use cases.
  • Architect and prototype AI and technical solutions on the Celonis platform, demonstrate business impact to C-suite executives, and ensure successful implementation, adoption, and value realization.
  • Translate domain expertise, product knowledge, and customer requirements into project execution; perform technical discovery and prototype bespoke AI solutions targeting industry-specific operational pain points.
  • Drive end-to-end execution of business-critical proof-of-value projects.
  • Deliver secure, scalable large language model and agent systems with retrieval-augmented generation, tools, and guardrails, integrating them with enterprise data, identity, and compliance frameworks.
  • Maintain technical and advisory involvement with strategic accounts through project completion, ensuring agreed value, adoption thresholds, and operational transformations are achieved.
  • Leverage domain expertise to build industry-specific end-to-end solutions and codify the work into reusable methodology and assets to accelerate team-wide time-to-value.

Desired Qualifications

  • Applied knowledge of linear and nonlinear optimization, statistical analysis, reinforcement learning, and forecasting.
  • Fluency in Dutch.
  • A Master's degree in computer science, engineering, mathematics, business engineering, business information, or a related field.

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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