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Celonis

Process intelligence platform for end-to-end efficiency

AI Solution Consultant New Grad

Pre-Sales Solution Engineering +1Posted on Nov 9
Full-time

About the Job

Requirements

  • A degree in Engineering, Data Analytics/Science, Computer Science, Mathematics, or a related STEM field.
  • Excellent academic performance.
  • Extensive internship experience or 1–2 years of full-time work experience, ideally at the intersection of business and technology.
  • Understanding of generative AI techniques such as retrieval-augmented generation, few-shot learning, prompt/context engineering, multi-agent orchestration, multimodal understanding, or fine-tuning, used to build use cases such as intelligent chatbots and automated text processors.
  • Good knowledge of Python, common machine-learning libraries such as LangChain, pandas, pydantic, scikit-learn, and PyTorch, as well as data engineering tools and technologies.
  • Analytical and creative problem-solving skills and the ability to apply technology to business challenges.
  • A customer-centric mindset focused on delivering value.
  • Confidence presenting to diverse audiences.
  • A proactive approach to problem-solving and willingness to learn from mistakes.
  • Curiosity, self-motivation, commitment to continuous learning, and readiness to work in a fast-paced, high-growth environment.
  • Strong organizational skills and ability to prioritize and execute on deadlines.
  • Excellent communication skills and business fluency in German and English.
  • Foundational business acumen and domain understanding, for example in supply chain.

Responsibilities

  • Understand customers’ AI strategies and business-critical challenges, identify suitable problem-solution fit, and translate customer requirements into solutions as a Celonis product and domain expert.
  • Use AI technologies to build creative prototypes in customer hackathons to solve business-critical problems.
  • Help customers achieve return on investment from AI deployments at scale by enabling a shift from rule-based automation to autonomous AI agents powered by the Celonis Process Intelligence Platform.
  • Execute business-critical Proof-of-Value projects end to end, demonstrating the value of Celonis Process Intelligence and aligning solutions with customers’ AI strategies.
  • Specialize in domains or industries, such as supply chain, to scale knowledge across the organization.
  • Present and quantify strategic business value to senior executives to support customer value realization.
  • Remain involved with projects until agreed value and adoption thresholds are reached.
  • Create reusable collateral, best practices, and tools for the Global Value Engineering Center of Excellence.
  • Build and code within the Celonis platform using SQL, PQL, and Python; scope business and technical requirements; handle objections; develop industry domain knowledge; deliver presentations and demos; support value selling and realization; and manage customer accounts.

Desired Qualifications

  • Degrees combining technical fields such as Computer Science or Data Science with business fields such as Economics or Marketing.
  • Customer-facing, customer success/service, or sales experience.
  • Hands-on experience with technical Proof-of-Concept projects.
  • Hands-on experience building agentic systems using large-language-model orchestration, retrieval-augmented generation, function calling, and prompt engineering.
  • Working knowledge of tools in the large-language-model ecosystem such as LangChain, LlamaIndex, or other open-source packages.
  • Supply chain process experience in procurement, order management, inventory management, or production.
  • Experience modeling return on investment and total cost of ownership for business case justification.
  • Experience with enterprise resource planning systems such as SAP or Oracle.

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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