Principal Agentic Data Systems Engineer

Salesforce Salesforce · Enterprise · Mexico City, Mexico

Salesforce is seeking a Principal Agentic Data Systems Engineer to architect and manage a private ecosystem of autonomous agents for ETL, synthetic data generation, automated QA, and predictive modeling. This role involves designing multi-step reasoning architectures, verification protocols, and managing hand-off protocols between specialized AI agents, acting as a central anchor for a hybrid human-agent intelligence unit. The engineer will also develop and maintain Model Context Protocol (MCP) servers for agent access to data sources.

What you'd actually do

  1. Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
  2. Design multi-step reasoning architectures and verification protocols to ensure agents autonomously validate and peer-review their own outputs.
  3. Transform high-level, ambiguous business requirements into production-ready data products independently, bypassing the need for mid-level project management.
  4. Use domain knowledge to ensure deployed tools are well governed. Governance as code for data pipelines and Agentic development. Context aware Agent development.
  5. Develop and maintain Model Context Protocol (MCP) servers to provide agents with secure, deep-link access to Snowflake, Salesforce, AWS, and proprietary internal data catalogs.

Skills

Required

  • Python
  • dbt
  • Airflow
  • advanced SQL
  • Apache Spark
  • Snowflake
  • AI-native development environments (e.g., Cursor, Codex, or Claude Code)
  • Prompt Engineering
  • agentic frameworks such as LangGraph
  • chain-of-thought prompting
  • self-correction loops
  • iterative reasoning paths
  • Salesforce Core and Data 360 understanding
  • Data Mesh
  • Data-as-a-Product (DaaP)
  • Event-Driven Architectures
  • Semantic layer
  • Knowledge Graphs
  • Docker
  • Kubernetes
  • serverless compute environments
  • 7+ years of experience in high-stakes Data Engineering, Architecture, or Data Science
  • Senior experience with Python & SQL
  • The ability to function as a "Domain Data Officer," managing end-to-end data strategy for a business unit with minimal supervision.
  • Superior analytical judgment

Nice to have

  • Generative AI

What the JD emphasized

  • production-grade proficiency
  • Expert in Prompt Engineering
  • Mastery of agentic frameworks
  • Expert-level knowledge
  • documented history of using generative AI to accelerate personal and departmental output by orders of magnitude
  • The ability to function as a "Domain Data Officer," managing end-to-end data strategy for a business unit with minimal supervision.

Other signals

  • autonomous agents
  • multi-agent ecosystems
  • orchestration
  • human-in-the-loop