AI Analytics Engineer (AI)

TL;DR

AI Analytics Engineer (AI): Building the infrastructure and context layer for AI-powered analytics to improve data accuracy and platform trustworthiness with an accent on semantic modeling, evaluation frameworks, and AI agent orchestration. Focus on designing autonomous data insights, building feedback loops for LLM-generated outputs, and scaling self-service capabilities across the business.

Location: Must be based in the United States

Salary: $141,600 – $193,600 USD

Company

hirify.global is a no-code app platform that powers critical business processes for over 500,000 organizations, including 80% of the Fortune 100.

What you will do

• Build and maintain context infrastructure including business glossaries and semantic layer definitions for AI models.
• Develop evaluation frameworks and accuracy benchmarks to ensure AI-generated insights are trustworthy.
• Orchestrate AI agent systems including prompt pipelines, tool routing, and guardrails for autonomous data querying.
• Design automated systems that proactively identify business patterns and anomalies.
• Drive cross-functional adoption of AI-powered analytics tools across GTM, Product, and Finance teams.
• Monitor query logs and usage patterns to identify gaps in context and expand self-service capabilities.

Requirements

• Strong SQL proficiency and experience with modern data tools like dbt, Databricks, or Snowflake.
• Strong written communication to translate business logic into structured, LLM-interpretable documentation.
• Hands-on experience with AI tools like Claude, ChatGPT, or Cursor applied to real work.
• Proven ability to partner with non-technical stakeholders to triage issues and drive tool adoption.
• Builder mindset with experience prototyping solutions and iterating quickly.
• 2-4 years of experience in data-related roles like Analytics Engineer, Data Analyst, or Data Scientist.

Nice to have

• Experience with BI semantic modeling tools such as Looker or Omni Analytics.
• Familiarity with Python and LLM APIs.
• Experience building automated evaluation or testing frameworks.
• Background in context engineering, knowledge management, or AI system design.
• Knowledge of ML concepts like time series analysis, statistical modeling, or anomaly detection.

Culture & Benefits

• Comprehensive benefits package including health insurance and equity (RSUs).
• Focus on innovation in an emerging AI analytics discipline.
• Equal opportunity employer committed to diversity and an inclusive workplace.
• Collaborative environment partnering across multiple business functions.
• Commitment to accessibility and reasonable accommodations during the hiring process.