# Associate Applied Value Engineer - Orbit Program

**Company:** [Celonis](https://hotfix.jobs/companies/celonis)
**Location:** Madrid, Spain
**Role:** Solutions Architecture
**Experience:** 0+ years
**Skills:** Python, SQL, Pql, RAG, Prompt Engineering, LangChain, pandas, Pydantic, scikit-learn, PyTorch, Llamaindex, Multi-Agent Orchestration, Function Calling, SAP, Oracle
**Posted:** 2026-08-27

> Build and present AI-powered Celonis solutions for strategic UK customers, from discovery and prototyping through Proof-of-Value delivery and adoption. The Orbit graduate program is suited to STEM graduates with strong Python and machine learning foundations, generative AI knowledge, and customer-facing communication skills.

## Job Description

## Responsibilities
- Discover and solution customer AI use cases by translating business and technical requirements into Celonis Process Intelligence solutions.
- Prototype AI solutions rapidly through customer hackathons and proof-of-concept projects.
- Enable agentic process transformation and help customers achieve measurable ROI from AI deployments at scale.
- Execute business-critical Proof-of-Value projects end to end, aligning solutions with customer AI strategies.
- Develop domain or industry expertise, such as supply chain processes.
- Present and quantify strategic business value to senior executives.
- Support projects through agreed value and adoption thresholds.
- Create reusable collateral, best practices, and tools for the Value Engineering Center of Excellence.
- Build and code on the Celonis platform using SQL, PQL, and Python.
- Scope requirements, handle objections, deliver demos, manage customer accounts, and develop customer relationships.

## Requirements
- Bachelor's degree in Engineering, Data Analytics, Data Science, Computer Science, Mathematics, or a related STEM field.
- Excellent academic performance.
- Extensive internship experience or 1–2 years of full-time work experience, ideally at the intersection of business and technology.
- Understanding of generative AI techniques including retrieval-augmented generation (RAG), few-shot learning, prompt or context engineering, multi-agent orchestration, multimodal understanding, and fine-tuning.
- Good knowledge of Python, common machine learning libraries, and data engineering tools.
- Strong analytical, creative problem-solving, communication, presentation, organizational, and prioritization skills.
- Customer-centric mindset, business acumen, curiosity, self-motivation, and willingness to learn.
- Fluent English communication skills.
- Foundational domain understanding, such as supply chain.

## Nice-to-haves
- Combined technical and business education.
- Customer-facing, customer success, service, or sales experience.
- Technical proof-of-concept experience.
- Experience building agentic systems with LLM orchestration, RAG, function calling, and prompt engineering.
- Familiarity with LangChain, LlamaIndex, or other open-source LLM packages.
- Supply chain experience in procurement, order management, inventory management, or production.
- Experience modeling ROI and total cost of ownership for business cases.
- Experience with SAP or Oracle ERP systems.

## Compensation and Benefits
- Restricted Stock Units and merit-based refresh grants for full-time employees.
- Paid parental leave, including 24 weeks for primary carers and 12 weeks for supporting carers.
- Unlimited PTO in applicable regions and generous paid time off globally.
- Flexible hybrid work model.
- Learning and development through the 70-20-10 learning framework.

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