Lead Agentic Data Systems Engineer

## About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. ## Role Overview **Lead Agentic Data Systems Engineer** **Location:** Mexico City | Full-Time | Hybrid **Department Overview** The Enterprise Data & AI Solutions group is the organization’s strategic hub for cognitive automation. We move beyond traditional data management to build the autonomous engines that power executive decision-making. Our team is composed of Architects of Autonomy—professionals with the technical depth to build systems from the ground up and the strategic vision to leverage AI to ensure scalability. We partner with the C-suite to solve high-complexity challenges by deploying sophisticated multi-agent ecosystems that operate with continuous uptime. **Role Description: The Builder** We are seeking a Lead Agentic Data Systems Engineer. This is a role for a hands-on, depth-first engineer who will take the architectural blueprints set by our Principal Engineers and turn them into hardened, production-grade data products. This role is defined by execution depth. You will own the product end-to-end — building it, maintaining it, enhancing it, and constructively challenging the design when implementation reality demands it. You are the person the business trusts to make a data product actually work, at quality, every day. You are someone who knows how to supercharge their own workflow with AI agents, but your primary leverage comes from deep, disciplined building rather than broad orchestration. **The Strategic Shift:** You are redefining the data team model. Instead of managing human personnel, you manage complex "hand-off" protocols between specialized AI agents, acting as the central anchor for a hybrid human-agent intelligence unit. ## Responsibilities * **Autonomous Scaling:** Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling. * **Agentic Orchestration:** Design multi-step reasoning architectures and verification protocols to ensure agents autonomously validate and peer-review their own outputs. * **Complex Problem Resolution:** Transform high-level, ambiguous business requirements into production-ready data products independently, bypassing the need for mid-level project management. * **Governance & Oversight:** Use domain knowledge to ensure deployed tools are well governed. Governance as code for data pipelines and Agentic development. Context aware Agent development. * **Contextual Integration:** 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. ## Requirements **Technical Profile** * **Engineering Foundation:** Production-grade proficiency in Python, dbt, Airflow, and advanced SQL. Apache Spark, and Snowflake. * **AI Orchestration:** Fluency in AI-native development environments (e.g., Cursor, Codex, or Claude Code). Expert in Prompt Engineering. Mastery of agentic frameworks such as LangGraph. Leverage MCP servers to retrieve data from tool stack. * **Cognitive Architecture:** Expert-level knowledge of chain-of-thought prompting, self-correction loops, and iterative reasoning paths. * **Salesforce Knowledge:** Salesforce Core and Data 360 understanding. * **Systems Design:** Advanced understanding of Data Mesh, Data-as-a-Product (DaaP), and Event-Driven Architectures. Semantic layer. Knowledge Graphs. * **Cloud Infrastructure:** Experience using agentic workloads via Docker, Kubernetes, and serverless compute environments. **Qualifications** * **Experience:** 5+ years of experience in high-stakes Data Engineering, Architecture, or Data Science. * **Strong Python / SQL Expertise** * **Operational Leverage:** A documented history of using generative AI to accelerate personal and departmental output by orders of magnitude. * **Strategic Autonomy:** The ability to function as a "Domain Data Officer," managing end-to-end data strategy for a business unit with minimal supervision. * **Technical Intuition:** Superior analytical judgment—the ability to identify subtle logic errors or hallucinations in agentic output before they reach production. ## Nice to Have * Experience with AI-native development environments (Cursor, Codex, Claude Code). * Mastery of agentic frameworks such as LangGraph. * Knowledge of Model Context Protocol (MCP). ## Benefits * Opportunity to work at the company leading workforce transformation in the agentic era. * Work with the Enterprise Data & AI Solutions group, the strategic hub for cognitive automation. * Partner with the C-suite to solve high-complexity challenges.