Airtable - Senior Solutions Architect
Requirements
• 5+ years of solution architecture, solution engineering, or technical consulting experience for enterprise SaaS platforms • Strong understanding of data modeling, database design, and governance • Experience designing workflow automation and operational systems • Familiarity with AI-enabled SaaS capabilities (LLMs, AI automation, AI-assisted workflows, or AI copilots) • Ability to translate complex business processes into scalable technical architectures • Strong stakeholder communication skills across technical and executive audiences • Experience scoping and delivering enterprise implementations • Proficiency in process mapping and architecture documentation tools (e.g., Lucidchart, Visio) • Experience designing AI-driven workflow solutions (LLMs, prompt design, AI agents, AI automation) • Experience implementing platforms like Airtable, Notion, ServiceNow, Salesforce, Workato, or similar workflow/data systems • Familiarity with APIs, integrations, and automation frameworks • Experience with enterprise data governance and security models • Experience in Professional Services or consulting organizations • Technical familiarity with scripting or low-code/no-code platforms • Experience developing repeatable architecture patterns or implementation frameworks
Responsibilities
• Architect and deliver paid SOW enterprise Airtable implementations for strategic customers • Lead scoping and design of Airtable AI solutions during professional services engagements • Develop repeatable AI solution patterns, including AI workflows, automations, and structured data pipelines • Establish best practices for data modeling, governance, and AI-enabled workflow design • Partner with Engagement Managers to scope services engagements and define implementation plans • Produce solution architecture diagrams, data models, and workflow documentation for enterprise customers • Drive adoption of Airtable AI capabilities across multiple enterprise implementations • Provide technical guidance and troubleshoot architectural challenges during implementations • Collaborate with Product and internal teams to relay AI feature feedback and influence the roadmap
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