AI Analytics Engineer (AI & Analytics… at Airtable · Syracuse-…

Summary: Airtable is a no-code app platform that empowers organizations to enhance their business processes. They are seeking an AI Analytics Engineer to build and maintain AI-powered analytics systems, ensuring that insights are trustworthy and scalable while driving cross-functional adoption of these tools. Responsibilities: - Build and maintain context infrastructure: Translate institutional business knowledge into structured formats — business glossaries, DBT model enrichment, semantic layer definitions in Omni Analytics — so that AI tools can answer questions accurately, not just confidently - Design and run evaluation frameworks: Develop predefined test cases, accuracy benchmarks, and validation workflows that measure whether AI-generated insights are trustworthy. Own the feedback loop between eval results and context improvements - Build and orchestrate AI agent systems: Help design, build, and iterate on the agent architectures that power our analytics tools — including prompt pipelines, tool orchestration, query routing logic, and guardrails that determine when AI should answer autonomously vs. escalate for human validation - Experiment and evaluate: Test prompt configurations, agent behaviors, and model outputs across different use cases — using eval results and accuracy metrics to drive continuous improvement - Develop internal AI tooling and workflows: Build tools and automations that improve DS&A's own efficiency — identifying opportunities where AI can accelerate the team's work and executing on them - Build automated insight generation systems: Design and develop AI-powered systems that proactively surface patterns, anomalies, and meaningful changes in business data — delivering the right insights to the right people without waiting to be asked. Think less 'answer questions' and more 'anticipate them.' - Drive cross-functional adoption: Partner with GTM, Product, Finance, and other teams to onboard users, field questions, triage issues, and train stakeholders on how to get the most out of our AI-powered analytics tools - Surface insights from usage patterns: Monitor query logs and user behavior to identify gaps in context coverage, recurring questions that should become standard reporting, and opportunities to expand self-service capabilities Required Qualifications: - 1–4 years of professional experience in data-related roles (analytics engineer, data analyst, data scientist, or similar) - Experience partnering with business stakeholders - Strong SQL proficiency - Experience working with modern data tools (dbt, Databricks, Snowflake, or similar) - Clear, structured writing — can translate complex business logic into documentation that both humans and LLMs can interpret - Hands-on experience with AI tools (Claude, ChatGPT, Cursor, or similar) beyond casual use — has applied them to build or accelerate real work - Cross-functional communication — can partner with non-technical stakeholders to understand needs, triage issues, and drive adoption - Builder mindset — comfortable picking up new technical skills, prototyping solutions, and iterating quickly Preferred Qualifications: - Experience in SaaS or tech environments - 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 (e.g., experimentation, time series analysis, statistical modeling, clustering, anomaly detection) Required Skills: SQL, dbt, Databricks, Snowflake, AI tools Claude, AI tools ChatGPT, AI tools Cursor, BI semantic modeling Looker, BI semantic modeling Omni Analytics, Python, LLM APIs, Evaluation/testing frameworks, Context engineering, Knowledge management, Agent architectures, Prompt engineering, AI system design, Data science concepts, Machine learning concepts, Cross-functional communication, Clear writing Benefits: The opportunity to receive benefits, Restricted stock units, May include incentive compensation