Senior Applied AI Solutions Architect - Process Intelligence (public Sector)

Celonis Celonis · Data AI · Paris, France · Value Engineering

Senior Applied AI Solutions Architect role at Celonis, a leader in Process Intelligence. This customer-facing role focuses on understanding customer objectives, identifying AI opportunities, designing AI-powered solutions using Celonis' PI platform and external AI/ML partners, prototyping, and driving adoption to deliver measurable business value. The role emphasizes problem framing, solution design, and business impact over pure software engineering, with some prototyping using Python and modern AI frameworks.

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
  • communicating 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), whether whiteboarding sessions or formal readouts and demos
  • 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 solutions
  • business value
  • AI
  • AI
  • AI
  • AI
  • AI
  • AI

Other signals

  • customer-facing
  • solution architecture
  • prototyping
  • business value
  • enterprise SaaS