Enterprise AI Value Architect for Transformation (Hybrid)

Celonis; Greater London; Hybrid; GBP 85,000 - 130,000; Full time

Benefits offered by this job

RSUs & refresh grants

Parental leave 24 weeks

Unlimited PTO

Flexible hybrid work

Learning platform access

Wellbeing programs

Impact Days

Inclusion & Belonging

Job summary

Celonis in the United Kingdom seeks an Applied Value Engineer to diagnose client challenges and prototype domain-specific AI use cases on the Celonis platform. You will architect and prototype AI/LLM solutions, demonstrate business impact to C-suite executives, and ensure adoption and measurable value realization across global accounts.

You will work on end-to-end PoV projects, align with security/compliance, and contribute to reusable methodologies, while benefiting from a flexible hybrid model

Qualifications

• Executive-Facing Presales & Value Engineering experience in PoV, ROI modelling, and executive pitching.

Responsibilities

• Discovery & AI Solutioning: translate requirements into projects and prototype AI solutions.
• AI Solution Development: lead PoV projects; deliver secure, scalable LLM/agent systems with RAG and enterprise data integration.
• Value Selling & Realization: maintain technical/advisory involvement to ensure value and adoption thresholds.

Skills

Presales

Domain knowledge

Python

Agentic AI

ML Ops

AI security

Operations research

Presentation

Education

Masters degree in CS, engineering, maths, business engineering or related fields

Tools

PyTorch

TensorFlow

scikit-learn

XGBoost

Hugging Face Transformers

AWS Bedrock

Azure AI

GCP Vertex AI

Job description

Celonis in the United Kingdom seeks an Applied Value Engineer to diagnose client challenges and prototype domain-specific AI use cases on the Celonis platform. You will architect and prototype AI/LLM solutions, demonstrate business impact to C-suite executives, and ensure adoption and measurable value realization across global accounts.

You will work on end-to-end PoV projects, align with security/compliance, and contribute to reusable methodologies, while benefiting from a flexible hybrid model