AI Customer Success Engineer

Overview

As an AI Customer Success Engineer, you bridge technology and business by embedding with users to understand workflows, build no-code automations, and drive AI adoption. You’ll analyze feedback, support rollout, and collaborate with product managers to deliver measurable AI value. This role sits at the intersection of user enablement, technical analysis, and enterprise impact. Join a growth‑minded, diverse team shaping rapid AI-enabled digital manufacturing solutions.

Pay / Benefits

• growth-oriented development
• extensive e-learning platform
• onsite car parking and transport links
• employee discount scheme
• wellbeing culture and psychologist support
• life insurance 4x base salary

Responsibilities

• Embed with business users to understand workflows and use cases for AI tooling
• Create and configure agents, apps and automations in no-code/low-code AI tooling with end-users
• Process and analyze user feedback to identify gaps between expectations and capabilities
• Develop onboarding materials and guide users through adoption
• Derive platform setup requirements based on user needs
• Oversee support channels and manage user questions
• Turn business challenges into no-code/low-code AI solutions from concept to implementation
• Support requirements analysis for AI use cases: elicit, document, refine, and validate
• Conduct demos and feedback calls with business users
• Define measurable KPIs and acceptance criteria for use case delivery
• Elicit, document, and translate functional and non-functional requirements through stakeholder interviews
• Produce clear requirement documents, process maps, and user guides

Key requirements

• Bachelor’s degree in a relevant field
• 3–5 years in customer success engineering, AI/digital solutions consulting, business analysis, or technical product enablement
• Hands-on experience building with no-code/low-code AI platforms (agents, automations, workflows, apps)
• Ability to independently deliver AI-powered solutions without custom development
• Cross-domain experience across manufacturing, engineering services, finance, HR, supply chain
• Strong understanding of enterprise system connections (APIs, integrations, data flows, SaaS)
• Excellent verbal and written communication; ability to present to non-technical audiences
• Proven ability to elicit, document, analyze, and validate requirements
• Natural ability to translate real-world challenges into structured use cases
• Ability to evaluate AI use cases for feasibility and value; know when to apply no-code vs custom dev
• Experience driving tool rollouts, user adoption programs, and change management
• Ability to produce requirement documents and process maps

• clear communication
• stakeholder facilitation
• workshops and demos
• no-code/low-code AI platforms
• LLM-based assistants
• prompt engineering

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