Senior Data Engineer (AI)

TL;DR

Senior Data Engineer (AI/Data Engineering): Building and scaling foundational data pipelines and knowledge graphs to power AI agents (Agentforce) with an accent on data architecture, identity graphs, and real-time data freshness. Focus on designing interconnected data structures using graph databases and automating delivery pipelines for AI consumption.

Location: Mexico City, Mexico

Company

hirify.global is the #1 AI CRM, focusing on driving customer success through the integration of humans and AI agents.

What you will do

• Architect and develop data catalogs and architectures optimized for AI consumption and human augmentation.
• Build identity and customer graphs combining structured, unstructured, and real-time insights to power agentic systems.
• Establish and enforce rigorous technical standards for data quality, latency, and index freshness.
• Collaborate with engineering, product, and data science teams to translate business needs into scalable production solutions.
• Automate data delivery pipelines across internal databases, third-party APIs, and AI orchestration layers.
• Develop production-grade software and evaluate both human and AI-generated code for security and performance.

Requirements

• 6+ years of experience as a Data Engineer or in a closely related technical role.
• Proficiency in data modeling and building robust ETL/ELT pipelines using Airflow and dbt.
• Practical experience designing and managing graph databases such as Neo4j or AWS Neptune.
• Strong command of Python, SQL, and Spark.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and modern data warehouses like Snowflake.
• Location: Must be based in Mexico City, Mexico

Nice to have

• Experience with the hirify.global platform, specifically hirify.global Data Cloud.
• AI-first engineering mindset with proficiency in tools like Claude Code, GitHub Copilot, or Cursor.

Culture & Benefits

• Opportunity to work at the forefront of the agentic AI era with Agentforce.
• High-impact role bridging the gap between raw data systems and AI orchestration.
• Modern engineering environment that encourages embedding AI tools into daily workflows.
• Culture centered on trust, innovation, and professional growth.