Currently tracking 3 active AI roles, down 57% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $177k–$278k (avg $228k).
| Title | Stage | AI score |
|---|---|---|
| AI Agent Architect, Customer Experience The AI Agent Architect will own the technical foundation for Airtable's AI-native customer support experience, focusing on designing and optimizing AI agent reasoning, retrieval, decision-making, and action execution. This involves architecting knowledge systems, decision logic, and guardrails for reliable and scalable AI resolution, with a strong emphasis on production systems and LLM fluency. | Agent | 8 |
| Senior Partner Solutions Architect Senior Partner Solutions Architect role focused on integrating AI capabilities, particularly agentic workflows, into partner-led solutions on the Airtable platform. The role involves solution architecture, customer/partner collaboration, AI/ML best practices, and partner enablement within the enterprise SaaS space. | Agent | 7 |
| Senior Partner Solutions Architect This role focuses on advising partners and customers on integrating AI capabilities, specifically agentic workflows, into Airtable solutions. The Senior Partner Solutions Architect will champion the use of Airtable's AI features, guide on AI/ML best practices and responsible AI, and stay updated on generative AI and machine learning trends relevant to the low-code/no-code space. The role also involves creating thought leadership content and enabling partners to build AI-powered solutions on the Airtable platform. | Agent | 7 |
| Product Security Engineer Product Security Engineer at Airtable, focusing on securing the application layer of their platform, including AI/LLM powered features. The role involves developing self-service security frameworks, automated guardrails, threat modeling, and securing LLM integrations. Experience in product security, web application security, and securing LLM integrations is required. | — | 5 |
| Software Engineer, Product Backend (8+ YOE) Software Engineer, Product Backend at Airtable, focusing on building systems for AI agents and integrations to interact with Airtable as a platform, making it a central hub for agentic workflows and data operations. | Agent | 5 |
| Senior Solutions Architect Senior Solutions Architect to partner with enterprise customers to design and implement complex, AI-enabled Airtable solutions. This role will lead the architecture and delivery of enterprise implementations, translating business workflows into scalable, AI-powered systems. Responsibilities include architecting and delivering paid SOW enterprise Airtable implementations, leading scoping and design of Airtable AI solutions, developing repeatable AI solution patterns, and driving adoption of Airtable AI capabilities. | Agent | 5 |
| Director, Technical Account Management Lead and scale a team of Technical Account Managers (TAMs) responsible for the technical relationship with strategic customers, focusing on how they build, deploy, and scale intelligent workflows on Airtable's platform. This role requires deep experience in platform architecture, integration, and hands-on fluency with AI agent capabilities, ensuring customers can run Airtable as mission-critical infrastructure. | Agent | 5 |
| Design Technologist This role focuses on evolving Airtable's design system and exploring AI's impact on UI development. The Design Technologist will build and ship components, develop AI tooling for UI coding (e.g., Claude skills, Cursor rules), and partner with cross-functional teams to improve user experience. The role requires a strong blend of design and engineering skills, with a focus on AI-assisted development workflows. | Ship | 5 |
| Software Engineer, Data Software Engineer, Data role focused on building and owning data pipelines for an AI-native platform. This includes instrumenting and measuring AI product usage, building event pipelines for AI agents, and developing AI-powered data discovery tooling like vector search. The role also involves using AI tools daily for pipeline development and debugging, and contributing to the data infrastructure that supports AI product analytics and business operations. | Data | 5 |
| Global Payroll Manager Airtable is seeking a Global Payroll Manager to lead and optimize end-to-end payroll operations across multiple global entities. The role involves ensuring payroll accuracy, compliance, and timely processing, building scalable processes, strengthening audit readiness, and partnering cross-functionally. A key aspect is leveraging AI or automation to streamline payroll processes and improve data accuracy. | — | 0 |
| Senior Accounting Manager This role is for a Senior Accounting Manager at Airtable. The primary focus is on transforming accounting operations through automation and AI-driven solutions to improve efficiency in financial reporting processes, including monthly close, accruals, flux analysis, and reconciliations. The role also involves supporting SOX compliance and financial audits. | — | 0 |
| Software Engineer, Compute (8+ YOE) Software Engineer to lead the next phase of platform maturity in how Airtable runs Kubernetes, focusing on building and evolving the compute platform infrastructure that powers Airtable’s services at scale. This role involves designing, implementing, and scaling core Kubernetes platform capabilities, leading modernization efforts, and improving developer experience around service creation and deployment. | — | 0 |
| Engineering Manager, Enterprise Product Engineering Manager for Airtable's Enterprise Product pillar, focusing on AI Governance. This role will lead a team responsible for building and scaling systems that provide enterprise customers with controls for AI adoption, including feature enablement, restrictions, and admin visibility. The role also involves scaling existing enterprise trust infrastructure like the Admin Panel, SSO, and audit systems. | — | 0 |
| Software Engineer, Infrastructure (4-8 YOE) Software Engineer, Infrastructure role at Airtable focusing on building and improving critical product infrastructure, including Kubernetes-based platforms that support AI services like vector databases and AI eval stores. The role involves working on compute, network stack, service discovery, disaster recovery, and developer platform tooling to enhance scalability, efficiency, reliability, and security. | — | 0 |