AI Analytics Engineer

AI Analytics Engineer (AI & Analytics Platform)

Airtable is seeking an AI Analytics Engineer to join its new AI & Analytics Platform team. This role is crucial for building the infrastructure that makes AI-powered analytics trustworthy and scalable. You will be one of the first hires shaping this new discipline, working at the intersection of data engineering, LLM tooling, and business enablement.

What You'll Do

• Build and maintain context infrastructure, translating business knowledge into structured formats for AI tools.
• Design and run evaluation frameworks to measure the trustworthiness of AI-generated insights.
• Build and orchestrate AI agent systems, including prompt pipelines and query routing logic.
• Experiment and evaluate prompt configurations, agent behaviors, and model outputs.
• Develop internal AI tooling and workflows to improve DS&A team efficiency.
• Build automated insight generation systems that proactively surface business data patterns.
• Drive cross-functional adoption by partnering with GTM, Product, Finance, and other teams.
• Surface insights from usage patterns to identify gaps and opportunities for self-service.

Who You Are

• Technically curious and AI-forward, with experience experimenting with LLMs and AI tools.
• A builder at heart with a bias for action and comfort picking up new technical skills.
• Analytically grounded with strong SQL proficiency and experience with modern data tools.
• Not married to legacy tooling, preferring to adopt new, effective approaches.
• A clear communicator and strong writer, capable of translating complex logic for humans and LLMs.
• Business-minded, genuinely curious about business operations and the metrics that matter.
• Energized by building something new in an emerging discipline and shaping best practices.
• Independent and proactive, able to own workstreams end-to-end and drive initiatives.

Experience

• 2 - 4 years in data-related roles (analytics engineer, data analyst, data scientist, or similar), including experience partnering with business stakeholders.
• Experience in SaaS or tech environments preferred.

Must-Have Skills

• Strong SQL proficiency and experience with modern data tools (dbt, Databricks, Snowflake, or similar).
• Clear, structured writing to translate complex business logic for humans and LLMs.
• Hands-on experience with AI tools (Claude, ChatGPT, Cursor, or similar) beyond casual use.
• Cross-functional communication skills to partner with non-technical stakeholders.
• Builder mindset, comfortable picking up new technical skills and prototyping solutions.

Nice to Have

• Experience with BI semantic modeling (Looker, Omni Analytics, or similar).
• Familiarity with Python and LLM APIs.
• Experience building evaluation or testing frameworks.
• Background in context engineering, knowledge management, or technical writing.
• Experience with agent architectures, prompt engineering, or AI system design.
• Familiarity with data science and ML concepts.

Key skills/competency

• AI Analytics Engineer
• LLM Tooling
• Data Engineering
• Business Enablement
• Context Infrastructure
• Evaluation Frameworks
• AI Agent Systems
• Prompt Engineering
• SQL
• dbt