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Celonis

Process intelligence platform for end-to-end efficiency

Lead Value Engineer

Pre-Sales Solution Engineering +1Confirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 8 years of experience leading technical pre-sales and post-sales engagements, preferably in healthcare, life sciences, pharmaceuticals, or medical technology. This includes defining AI roadmaps, building return-on-investment and total-cost-of-ownership business cases, and guiding technical implementations through value realization.
  • Expertise in generative AI techniques such as retrieval-augmented generation, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning to build high-impact use cases.
  • Solid knowledge of Python and advanced predictive analytics techniques, such as LangChain, pandas, pydantic, scikit-learn, and PyTorch, as well as data-engineering tools and technologies for working with large, siloed datasets to build predictive algorithms and tools.
  • Strong presentation skills for internal and external stakeholders, including supply-chain executives and IT leaders, in technical whiteboarding sessions, formal readouts, and demonstrations.
  • A bachelor's degree is required.
  • Hands-on experience building agentic systems using large language model orchestration, retrieval-augmented generation, function calling, and prompt engineering, with rigorous safety evaluations suitable for regulated GxP life sciences environments.
  • Working knowledge of tools in the large-language-model ecosystem, such as LangChain, LlamaIndex, or other open-source packages.
  • Experience deploying and monitoring models at scale across major cloud platforms such as AWS Bedrock, Azure AI, or GCP Vertex.

Responsibilities

  • Understand the client's overarching AI strategy and business-specific challenges, and translate complex, multi-tiered requirements into innovative AI solutions as a Celonis product expert.
  • Use data in the Celonis Context Model to design and deploy time-series forecasting, optimization, and predictive algorithms for complex logistics constraints, such as dynamic inventory routing and schedule optimization.
  • Lead the customer lifecycle, including technical discovery and capability demonstrations during pre-sales, and guide post-sale implementation to meet supply-chain value and adoption thresholds.
  • Build prototypes using AI technologies in customer hackathons to address planning, sourcing, manufacturing, and distribution challenges in fragmented supply-chain networks.
  • Help customers achieve return on investment from scaled AI deployments by enabling autonomous AI agents on the Celonis Process Intelligence Platform, including use cases such as autonomous inventory rebalancing and shipment-exception handling.
  • Execute business-critical Proof-of-Value projects end to end, including architecting and delivering secure, scalable large-language-model and agent systems with retrieval-augmented generation, tools, and guardrails, integrated with enterprise systems of record.

Desired Qualifications

  • A master's degree in computer science, supply-chain management, engineering, mathematics, or a related field, or equivalent work experience.

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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