Senior Applied AI Engineer

Key Responsibilities

• Actively drive the full customer lifecycle: lead technical discovery and capability demonstrations during pre-sales expansion cycles and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are met.
• Own driving enterprise-wide ROI and adoption programs; accelerate customer autonomy through QBRs, strategic roadmaps, and enterprise-wide value opportunities.
• Serve as the internal and external technical subject matter expert for customer industry domain to scale knowledge across the organization.
• Understand customers' AI strategies and specific challenges; as a Celonis product expert, find the best problem-solution fit and translate customer requirements into innovative solutions that deliver measurable impact.
• Blend process and industry expertise with a solution-first mindset, analyzing customer data and deploying tactical solutions using the Celonis Process Intelligence platform to feed critical operational context to AI and LLM tools.
• Help customers move past simple automation to deploy intelligent, autonomous agents that solve complex business bottlenecks.
• Manage weekly cadences, QBRs, and value plans to demonstrate the value of solutions to VP+ level executives.
• Plan and manage project scope, expectations, and timelines across multiple projects at different parts of the value journey; leverage partners from the Celonis Ecosystem.

Requirements

• 4+ years of experience in pre-sales, customer success, and/or consulting functions with a background in pre/post-sales consulting, strategy consulting, business process improvement, digital transformations, or customer value realization.
• Strong technical skills across Microsoft or competitor equivalent (e.g., AWS) with certification in relevant technologies (e.g., Azure, Data Engineering). Knowledge of Data Connections, Data Objects, Data Validation, and Data Analysis.
• Knowledge and use of LLMs (e.g., Claude, Copilot); understanding of basic prompting and data constructs within a prompt.
• Value-driven selling through expertise in identifying and prioritizing use cases, implementing improvement measures, and becoming a change agent by establishing an operating model and training users to realize value and renew/expand subscription.
• Ability to plan and manage multiple projects across aligned accounts.
• Strong presentation skills for both internal and external stakeholders, including technical whiteboarding sessions, formal readouts, and demos.
• Bachelor’s Degree required; focus in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice-to-Haves

• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, sklearn, PyTorch) as well as data engineering tools and technologies.
• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.