Senior Value Engineer- Healthcare Distribution

Celonis Celonis · Data AI · New York, NY · Value Engineering

This role focuses on applying AI and ML, specifically generative AI techniques like RAG and multi-agent orchestration, to solve complex supply chain and logistics problems within the healthcare distribution industry. The Senior Value Engineer will work with clients to understand their challenges, prototype AI solutions using Celonis' Process Intelligence platform and partner AI technologies, demonstrate value, and ensure successful implementation and adoption at an enterprise scale. The role involves both pre-sales and post-sales activities, hackathons, and building agentic process transformations.

What you'd actually do

  1. Understand the client's overarching AI strategy and the distinct supply chain challenges inherent to healthcare wholesale (e.g., predictive demand forecasting for generic and brand pharmaceuticals, optimizing distribution center throughput, navigating complex contract pricing, or managing acute care logistics). As a Celonis product and distribution domain expert, translate these high-volume logistics requirements into innovative AI solutions that drive measurable impact.
  2. Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle across various distribution and operational business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached in both corporate and warehouse environments.
  3. Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and fulfillment networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, procurement, and customer service.
  4. Support the client in achieving tangible ROI from AI at an enterprise scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous resolution of order-to-cash disputes, intelligent backorder handling, or automated warehouse exception management).
  5. End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs, Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and strict regulatory track-and-trace frameworks (e.g., DSCSA).

Skills

Required

  • 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, Logistics, or Wholesale Distribution environments
  • Deep understanding of supply chain business processes native to high-volume distribution
  • Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases
  • Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch)
  • Strong presentation skills

Nice to have

  • Healthcare/Pharma distribution preferred
  • Master's Degree in computer science, supply chain management

What the JD emphasized

  • highly complex Supply Chain, Logistics, or Wholesale Distribution environments
  • Healthcare/Pharma distribution preferred
  • AI roadmaps
  • ROI/TCO business cases
  • value realization
  • supply chain business processes native to high-volume distribution
  • generative AI techniques
  • RAG
  • multi-agent orchestration
  • fine-tuning
  • high-impact use cases
  • massive, high-velocity transactional supply chain datasets
  • DSCSA

Other signals

  • industrialize AI
  • unlocking real ROI on deployments at scale
  • enterprise scale
  • autonomous AI agents