Senior Strategic Value & Process Optimisation Consultant

Celonis Celonis · Data AI · Stockholm, Sweden · Value Engineering

Customer-facing role focused on identifying, designing, prototyping, and driving adoption of AI-powered solutions for enterprise clients using Celonis' Process Intelligence platform and external AI/ML partners. The role emphasizes delivering measurable business value and translating complex challenges into practical AI solutions, with a focus on Generative AI architectures like RAG and agent-based systems.

What you'd actually do

  1. Identify High-Impact AI Opportunities: Work closely with enterprise customers to understand their strategic priorities and operational challenges, identifying where AI can deliver measurable business value.
  2. Design AI-Powered Solutions: Translate complex business problems into scalable AI solution architectures combining the Celonis Process Intelligence platform with modern AI technologies.
  3. Prototype & Demonstrate Value: Rapidly build prototypes and proof-of-value solutions that demonstrate tangible outcomes to business and technical stakeholders.
  4. Lead AI Innovation with Customers: Facilitate workshops, hackathons, and innovation sessions with customers to explore new ways AI can transform their operations.
  5. Drive Adoption and Business Impact: Partner with customer teams to ensure successful implementation, adoption, and realization of measurable value from AI deployments.

Skills

Required

  • 5+ years of experience in solutions consulting, data / AI consulting, technical pre-sales, sales engineering, value engineering, or customer-facing solution-architecture or AI roles
  • translating business challenges into technical solutions
  • communicate complex technical concepts to business and executive stakeholders
  • 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
  • strong presentation skills to both internal and external stakeholders (including executives)
  • prototyping solutions with Python and modern AI frameworks
  • Generative AI architectures such as RAG, prompt engineering, or agent-based systems

Nice to have

  • Experience building or deploying generative AI applications
  • Familiarity with tools such as LangChain, LlamaIndex, or other LLM orchestration frameworks
  • Industry experience in domains such as supply chain, finance, or operations
  • Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience

What the JD emphasized

  • customer-facing
  • AI
  • AI solutions
  • AI can deliver measurable business value
  • AI-Powered Solutions
  • AI technologies
  • AI Innovation
  • AI can transform their operations
  • AI deployments
  • AI roles
  • AI use cases
  • AI frameworks
  • Generative AI architectures
  • generative AI applications

Other signals

  • customer-facing
  • prototyping AI solutions
  • delivering meaningful value for customers
  • enterprise customers
  • AI can deliver measurable business value
  • scalable AI solution architectures
  • modern AI technologies
  • tangible outcomes
  • business and technical stakeholders
  • new ways AI can transform their operations
  • successful implementation, adoption and realization of measurable value from AI deployments
  • develop domain expertise
  • Python and modern AI frameworks
  • Generative AI architectures such as RAG, prompt engineering, or agent-based systems
  • building or deploying generative AI applications
  • LLM orchestration frameworks