AI Agent Architect, Customer Experience

About Airtable

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done.

Join Airtable as an AI Agent Architect, Customer Experience and own the technical foundation that powers our AI-native customer support experience. You'll design and optimize how our AI agents reason, retrieve, decide, and act—architecting the knowledge systems, decision logic, and guardrails that enable reliable, scalable AI resolution at scale. This role requires deep fluency in how large language models work, hands-on experience with AI agent architectures, and the ability to partner closely with Engineering on production systems.

What You'll Do

• Own Agent retrieval accuracy and relevance: Architect the knowledge systems that enable AI agents to surface the right answer on the first try. Measure and improve retrieval precision, contextual relevance, and hallucination rates.
• Drive automated resolution rates: Build the decision frameworks that allow agents to take confident actions. Define API access, account modification policies, and encode business logic into auditable, predictable systems that resolve issues without human intervention.
• Manage AI safety and trust: Establish guardrails to maintain high resolution rates and low failure rates. Prevent edge cases, block prompt injection, and mitigate unintended behaviors.
• Own the feedback loop: Monitor the observability layer to turn agent behavior into actionable insights. Instrument retrieval accuracy, action success rates, and failure patterns to drive measurable week-over-week improvements in agent performance.
• Continuously improve agent quality: Develop and maintain the prompt architecture governing how agents reason and respond. Implement systematic approaches to versioning, A/B testing, and performance evaluation, measuring consistency, accuracy, and adaptability.
• Drive integration strategy: Architect how agents connect to external systems like billing platforms, CRMs, internal tools, and Airtable APIs. Define authentication patterns, error handling, and data transformation, with accountability for uptime, error rates, and data accuracy.

Who You Are

• You deeply understand large language models—their reasoning, failures, and underlying mechanisms, beyond just their use. Familiarity with RAG architectures, prompt engineering, chain-of-thought reasoning, and agent frameworks is key. You have built or significantly contributed to production AI-powered systems.
• You think in terms of data flows, state management, error handling, and edge cases, capable of designing powerful and reliable complex systems. Experience in solutions architecture, platform engineering, or technical program management is highly relevant.
• You are proficient in scripting, working with APIs, querying databases, and prototyping solutions independently. While not a full-time software engineer, you can build, test, and validate technical approaches, instrument systems, analyze logs, and use data to diagnose issues and validate improvements. You can build dashboards, define metrics, and connect technical changes to business outcomes like resolution rates and customer satisfaction.
• You can clearly explain complex AI system behavior to non-technical stakeholders, write concise technical documentation, and translate business requirements into system specifications. You are effective collaborating across engineering, product, and operations teams.

Key skills/competency

• AI Agent Architectures
• Large Language Models (LLMs)
• Retrieval Augmented Generation (RAG)
• Prompt Engineering
• System Design
• Data Analysis
• API Integration
• Customer Experience (CX)
• Observability
• Technical Program Management