Role Description

• As an Applied AI Engineer specializing in Healthcare Distribution and Logistics, you are pushing the envelope in solving business-critical problems for one of the world's largest healthcare wholesale and distribution enterprises. You will be working intimately with this strategic client, understanding their uniquely complex objectives—spanning from high-volume warehouse optimization and pharmacy fulfillment to ensuring seamless hospital supply logistics and DSCSA compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customer's massive, high-velocity distribution network. This enables them to industrialize AI, unlocking real ROI on deployments at scale, and ultimately ensuring critical medicines and medical supplies reach care providers and patients without delay. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Supply Chain SVPs and logistics leaders, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis within this premier healthcare distribution network.

Key Responsibilities:

• AI Discovery & Solutioning: 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.

• Pre- and Post-Sales Execution: 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.

• Hackathons & Prototyping: 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.

• Agentic Process Transformation: 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).

• Proof Projects: 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).

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for Healthcare Distribution, scaling knowledge across the organization regarding the nuances of medical/surgical and pharmaceutical wholesale operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, Logistics, or Wholesale Distribution environments (Healthcare/Pharma distribution preferred). This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume distribution (such as Order-to-Cash, Procure-to-Pay, Inventory Management, Warehouse Operations, or Transportation Logistics) with the ability to translate high-level operational needs into specific AI use cases.

• 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 (e.g., intelligent chatbots for pharmacy/hospital customer support, or automated extraction of data from complex vendor contracts and rebate agreements).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional supply chain datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, warehouse directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for highly regulated healthcare logistics environments.

• Familiarity with distribution-specific systems and standards (e.g., Manhattan, Blue Yonder, SAP EWM, and DSCSA track-and-trace serialization data).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
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