Senior Applied AI Engineer
Lead Applied Value Engineer partnering with enterprise customers and sales teams to drive end-to-end value realization using Celonis Process Intelligence platform and AI/LLM tools. Responsibilities include technical discovery, AI solutioning for agentic systems, ROI programs, QBRs, and executive presentations; requires 4+ years in pre-sales/consulting with strong technical and presentation skills.
About the job
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.
Skills
LLMs, Python, LangChain, pandas, scikit-learn, PyTorch, RAG, Prompt Engineering, Azure, AWS, Data Engineering, Process Mining
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