The opportunity
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity.
What you'll do
AI Discovery & Solutioning: Understand the client's overarching AI strategy and the distinct challenges that are distinct to their business. As a Celonis product expert, translate these complex, multi-tiered 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 pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds in the supply chain are successfully reached.
Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex, fragmented supply chain networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points in planning, sourcing, manufacturing, and distribution.
Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., autonomous inventory rebalancing or intelligent shipment exception handling).
Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise systems of record.
+ years of experience leading technical pre-sales and post-sales engagements: preferred within Healthcare, Life Sciences, Pharmaceutical, or MedTech. This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.
What they're looking for
- 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 supplier collaboration, automated extraction of data from complex customs or quality documents).
- Solid knowledge of Python and Advanced Predictive Analytic techniques (such: as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for leveraging massive, siloed datasets to build algorithms and tools aimed at predicting future business outcomes.
- Strong presentation skills to both internal and external stakeholders: (including supply chain executives and 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, engineering, mathematics, or related fields, or equivalent work experience preferred.
