AI-Driven Delivery Architect

Airtable; United States; Remote; USD 120,000 - 150,000; Full time

Job summary

Airtable is seeking a Delivery Consultant to turn solution visions into operating systems, interfaces, automations, data models, and integrations. You will lead customer sessions, translate design into practical systems, and ensure delivery quality with AI-enabled capabilities.

Ideal candidates have hands-on technical depth, 3-5 years in client-facing delivery, and the ability to speak to how systems perform in practice, not just how they were designed.

Qualifications

• AI is embedded in how you build, not something you reach for on select tasks.
• 3-5 years in a client-facing delivery or implementation role, with direct accountability for whether systems work in practice.

Responsibilities

• Run recurring customer sessions with the operators and builders who will live in the system, surfacing the ground-level realities that change what gets built and how.
• Build the interfaces, field agents, automations, data models, and integrations that translate a solution vision into working systems.
• Make the calls that close the gap between designed and real: when user feedback signals a design issue, bring the solution, not just the flag.
• Build efficiently with AI.
• QA your own work against how users will actually behave, not just whether automations fire correctly.
• Create reusable build patterns that extend impact beyond individual engagements.
• Achieve full Airtable platform proficiency within 90 days; advanced work across interfaces, automations, data modeling, and integrations is the baseline expectation.

Job description

Airtable is seeking a Delivery Consultant to turn solution visions into operating systems, interfaces, automations, data models, and integrations. You will lead customer sessions, translate design into practical systems, and ensure delivery quality with AI-enabled capabilities.

Ideal candidates have hands-on technical depth, 3-5 years in client-facing delivery, and the ability to speak to how systems perform in practice, not just how they were designed.