Senior AI & Automation Specialist
AutodeskKraków, POLPosted 15 April 2026
Tech Stack
Job Description
Job Requisition ID #
26WD97212
***Please submit your CV in English***
Position Overview
The Senior AI & Automation Specialist will bring a strong background in artificial intelligence, knowledge systems, automation, and workflow design. This role will focus on applying AI to improve how Customer Success teams access the guidance, policy, process, and operational information they need, while also driving more scalable content, workflows, and team solutions through practical automation.
This role will help evolve how support is delivered across Customer Success by improving knowledge capture, structure, accessibility, and reuse, and by identifying opportunities where AI-enabled self-service can reduce friction and improve the day-to-day experience of field teams. In parallel, the role will help strengthen internal team efficiency by building repeatable workflows, templates, and automation solutions that improve consistency, quality, and scale.
The role will partner closely with Customer Success Readiness, policy and process owners, operations, content teams, and cross-functional stakeholders to design practical, responsible, and scalable AI-enabled solutions that improve knowledge access, team productivity, and overall support effectiveness.
Key Responsibilities
Identify and implement AI, automation, and knowledge design opportunities that improve how Customer Success teams access policy, process, and operational guidance
Help evolve more scalable support experiences that strengthen self-service and reduce reliance on repetitive human-to-human support
Design and maintain reusable workflows, templates, and tools to support readiness, content development, knowledge sharing, and operational efficiency
Apply generative AI capabilities to improve knowledge access, content scalability, workflow support, and team productivity
Partner with policy, process, and content owners to improve how knowledge is captured, structured, maintained, and governed for AI-enabled use cases
Support integration with platforms and tools such as Airtable and other automation or knowledge management solutions
Drive AI evangelism and adoption through practical use cases, stakeholder partnership, and clear guidance for responsible AI usage
Define and track success measures, including adoption, productivity, self-service effectiveness, and reduction in repetitive support requests
Minimum Qualifications
Bachelor’s degree in Education, Knowledge Management, HCI, Computer Science, Data Science, AI/ML, Business Systems, or a related field, or equivalent practical experience
3 years of experience in applied AI, automation, knowledge systems, workflow design, or related roles
Experience applying generative AI to knowledge access, content delivery, workflow support, business productivity, or customer-facing use cases
Experience designing or improving knowledge management, content structures, taxonomies, or information architecture
Experience with automation platforms and tools such as Airtable, Zapier, Make, or similar solutions
Familiarity with APIs, data structures, and workflow integration concepts
Strong analytical, problem-solving, communication, and collaboration skills
Ability to translate ambiguous business needs into practical, scalable solutions
Preferred Qualifications
Experience supporting Customer Success, customer-facing, support, enablement, readiness, or operations teams
Familiarity with Customer Success workflows, support models, and field team needs is a strong plus
Experience improving self-service, knowledge access, or support experiences through AI, automation, or digital solutions
Experience partnering with policy, process, or operations teams to improve knowledge capture, usability, and governance
Familiarity with Airtable scripting, JavaScript, or lightweight technical configuration
Experience driving adoption of new tools, processes, or ways of working across teams
Understanding of responsible AI practices, incl ... (truncated, view full listing at source)
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