Principal Agentic Data Systems Engineer

TL;DR

Principal Agentic Data Systems Engineer (AI/Data): Architect and maintain private ecosystems of 10+ autonomous agents for ETL, synthetic data generation, automated QA, and predictive modeling with an accent on multi-agent orchestration, verification protocols, and governance as code. Focus on designing multi-step reasoning architectures, transforming ambiguous business requirements into production-ready data products, and developing Model Context Protocol servers for secure data access.

Location: Mexico City | Hybrid

Company

The Enterprise Data & AI Solutions group is the strategic hub for cognitive automation, building autonomous engines that power executive decision-making with multi-agent ecosystems.

What you will do

• Architect and maintain ecosystems of autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
• Design multi-step reasoning architectures and verification protocols for agents to validate and peer-review outputs.
• Transform high-level business requirements into production-ready data products independently.
• Implement governance as code for data pipelines and agentic development, ensuring context-aware agent building.
• Develop and maintain Model Context Protocol servers for secure access to Snowflake, hirify.global, AWS, and internal data catalogs.
• Orchestrate agent fleets for complex tasks like market stress tests, knowledge retrieval, and self-healing security systems.

Requirements

• 7+ years in high-stakes Data Engineering, Architecture, or Data Science.
• Production-grade proficiency in Python, dbt, Airflow, advanced SQL, Apache Spark, and Snowflake.
• Fluency in AI-native tools (Cursor, Codex, Claude Code), prompt engineering, and agentic frameworks like LangGraph.
• Expert knowledge of chain-of-thought prompting, self-correction loops, Data Mesh, DaaP, event-driven architectures, and knowledge graphs.
• Experience with Docker, Kubernetes, serverless compute, and hirify.global Core/Data 360.
• Proven use of generative AI to accelerate output and ability to manage end-to-end data strategy autonomously.

Culture & Benefits

• Operate as a Human-in-the-Loop Orchestrator, achieving output of a 3-5 person team through agentic workflows.
• Focus on high-level design and supervision rather than manual coding.
• Build self-healing digital immune systems and asynchronous long-tail tasks for continuous uptime.
• Partner with C-suite on high-complexity challenges in a hybrid human-agent intelligence unit.