Lead Agentic Data Systems Engineer

What you'll do

• - Architect and maintain a private ecosystem of 10+ autonomous agents for ETL, synthetic data generation, QA, and predictive modeling.
• - Design multi-step reasoning architectures to ensure AI agents autonomously validate and peer-review their own outputs.
• - Transform high-level business requirements into production-ready data products independently without mid-level project management.
• - Develop governance strategies using domain knowledge to ensure deployed tools are well governed with code-based oversight.
• - Create and maintain Model Context Protocol (MCP) servers for secure, deep-link access to various data sources.

What we're looking for

• 5+ years of experience in high-stakes Data Engineering, Architecture, or Data Science.
• Proficiency in Python, dbt, Airflow, advanced SQL, Apache Spark, and Snowflake.
• Expertise in AI-native development environments and agentic frameworks like LangGraph.
• Advanced understanding of Data Mesh, Data-as-a-Product (DaaP), and Event-Driven Architectures.
• Experience managing complex "hand-off" protocols between specialized AI agents.
• Fluency in Salesforce Core and Data 360 with a documented history of using generative AI.
• Superior analytical judgment to identify logic errors or hallucinations in agentic output.