Job Specifications
Description
About Salesforce:
We’re Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.
About The Role
We are seeking a technically adept and innovative Agentic Data Specialist to join our Forward Deployed Engineering Team. You will serve as the crucial link between our advanced AI agents and the wider enterprise technology landscape. Your primary responsibility will be to design, build, and manage the data and integrations that enable our Agentforce agents to take meaningful, autonomous actions across various business systems.
You will not only connect agents to systems but also orchestrate a collaborative network of specialized AI agents, ensuring they work together seamlessly to solve complex business problems. If you are an expert in connecting disparate systems and are excited by the challenge of enabling AI to act upon its insights, this role is for you.
As an Agentic Data Specialist, you will serve as the crucial link between our advanced AI agents and the wider enterprise technology landscape. Your primary responsibilities will focus on designing, building, and managing the data, systems, and logic that enable our Agentforce solutions to take meaningful, autonomous actions.
Your Impact
Data Flow and Transformation: Manage the real-time flow of data to and from the AI agent. Implement necessary data transformations to ensure compatibility between different system formats and schemas.
Architect AI Grounding Systems: Design, build, and maintain cutting-edge AI data integration technologies, including RAG (Retrieval-Augmented Generation), vector databases, search indexes, and knowledge bases, specifically to ground Agentforce solutions with accurate, real-time enterprise data.
Orchestrate Multi-Agent Systems & Communications: Define the technical architecture and protocols (including Model Context Protocol and Agent-to-Agent Communication) to govern, monitor, and ensure efficient collaboration among specialized AI agents.
System & Agent Integration Architecture: Design and implement robust, scalable, and secure data integration patterns that connect Agentforce to a wide range of enterprise applications and enable communication between different AI agents.
Define LLM Strategy: Leverage comprehensive knowledge of the LLM (Large Language Model) landscape to evaluate, select, and optimize major foundational and frontier models for ideal application scenarios within enterprise AI deployments.
Ensure Salesforce Data Governance: Apply deep data management expertise to ensure the secure integration, transformation, and governance of structured and unstructured data within the Salesforce ecosystem (CRM, Data Cloud) and external systems.
Build Scalable and Secure Systems: Apply knowledge of message queues, event-driven architecture, and distributed systems to build resilient workflows, while implementing and managing secure authentication and authorization protocols (OAuth, SAML)to ensure that all agent actions are secure and comply with enterprise security policies.
API Development and Management: Develop, deploy, and maintain custom APIs (REST, SOAP, webhooks) to facilitate seamless data exchange and action execution between Agentforce and other systems.
Enable Workflow Automation: Collaborate with business analysts and AI specialists to translate complex business processes into automated, agent-driven workflows. Implement the technical logic that enables agents to perform tasks like creating records, triggering notifications, and updating systems.
Troubleshooting and Optimization: Monitor the health and performance of integrations, proactively identifying and resolving issues. Continuously optimize integration workflows for speed, reliability, and efficiency.
Required Qualifications
5+ years of hands-on experience in data engineering or integrations, such as a Data Engineer, Data Architect or Data Scientist.
High level of proficiency with one or more programming/scripting languages (e.g., Python, Java, JavaScript).
Expertise in AI data integration, including RAG, vector databases, search indexes, and knowledge bases, specifically for grounding Agentforce solutions with enterprise data.
Deep understanding of structured and unstructured data management within the Salesforce ecosystem (CRM, Data Cloud) and external systems, encompassing integration, transformation (ETL/ELT), and governance.
Current, comprehensive knowledge of the LLM landscape, including the specifications, capabilities, and ideal use cases for major foundational and frontier models re