Applied AI Engineer

About the job

We're Celonis, the global leader in Process Intelligence technology and one of the world's fastest-growing SaaS firms. We believe there is a massive opportunity to unlock productivity by placing AI, data and intelligence at the core of business processes - and for that, we need your help. Role Description As an Applied AI Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI, unlocking real ROI on AI deployments and at scale. There is no AI without PI. Key Responsibilities: AI Discovery & Solutioning: Understand customers' AI strategy and business-critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle. Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons solving business-critical problems. Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform. Proof projects: End-to-end execution of business-critical Proof-of-Value projects, including architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks. Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached. Specialize in Domains or Industries: To scale knowledge across the organization, Applied AI Engineers specialize in domains (e.g., supply chain) and industries. Requirements: 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions. Understanding of generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning is used to build high-impact use cases like intelligent chatbots and automated text processors. Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies. Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos. Bachelor’s Degree required; Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.