Description
As a Forward Deployed Engineer (FDE) focusing on Agentforce Operations (Regrello), you are a hands-on Technical Builder who designs, constructs, and deploys enterprise-grade agentic AI solutions directly inside customer environments. Agentforce Operations (formerly Regrello) converts manual, document-driven processes into agent-executed workflows across teams and systems.
You will serve as the crucial link connecting advanced AI agents to the broader enterprise technology landscape. You will write production code, architect real-time data grounding systems, perform prompt engineering, manage multi-agent communication protocols, and deploy automated supply chain and back-office workflows into production from day one.
You'll thrive here if you can understand and map a customer's process, model it as agentic workflows, and build the thing yourself.
What You'll Actually Be Building
Workflow & Multi-Agent Orchestration: Build, configure, and optimize complex operational workflows using Agentforce Operations (Regrello), defining agent reasoning, tool-calling logic, and conditional execution loops.
Agent Communication Protocols: Implement modern agent-to-agent communication standards and the Model Context Protocol (MCP) to govern context sharing, task hand-offs, and tool execution across specialized AI agents.
Enterprise AI Grounding Systems: Architect, build, and maintain real-time data grounding infrastructure using RAG (Retrieval-Augmented Generation), vector databases, search indexes, and knowledge bases to supply agents with accurate enterprise context.
Enterprise Integration & API Management: Develop and maintain custom APIs (REST, GraphQL, webhooks) and integration pipelines connecting AFO/Agentforce to Salesforce Data Cloud (Data 360), cloud warehouses (Snowflake, Databricks), and core ERPs (SAP, Oracle, NetSuite) via MuleSoft or custom middleware.
AI-Assisted Engineering: Leverage modern AI tools (Cursor, Claude, Vibes) embedded directly into your daily developer workflow to move from architecture sketch to deployable code in days, not months.
Telemetry & Observability: Model data, ship ETL/ELT pipelines, and build real-time agent performance dashboards to track execution health, fallback triggers, and business outcomes.
Field-to-Product Feedback: Serve as the direct connective bridge between frontline customer deployments and core Salesforce product/engineering teams to feed edge cases and gaps back into platform feature roadmaps.
Required Qualifications
7+ years professional experience
Hands-on AI & Grounding Expertise: Deep experience with LLM orchestration, prompt tuning, and building RAG pipelines, vector search indexes, and knowledge base retrievers for enterprise data.
Multi-Agent Systems & API Mastery: Practical experience with API design (REST/SOAP/webhooks) and modern agent protocols (e.g., MCP, tool calling, or event-driven messaging architectures).
Expertise in process orchestration and API-led connectivity using tools like MuleSoft or custom middleware to bridge AI agents with legacy ERP systems.
Solid understanding of data modeling, schema design, and asynchronous message integration patterns.
Familiarity with automation platforms (for example, Pega, UiPath, Automation Anywhere, ServiceNow, Appian, Microsoft Power Platform) and competing enterprise AI and agent platforms (Microsoft Copilot Studio, Google Vertex AI, AWS Bedrock, IBM watsonx, Palantir AIP, ServiceNow AI Agents).
Experience with integrated enterprise applications (for example, Workday, Coupa, Jira, Slack, major warehouse or transportation management systems)
Knowledge of data governance and master data systems (Informatica, Collibra, SAP MDG, Reltio) and operational execution platforms (Manhattan Associates, Blue Yonder, Kinaxis, Oracle transportation management).
Willingness to travel 25-30% for on-site deployment with key enterprise accounts.
Preferred Qualifications
Specific domain expertise in Supply Chain, Manufacturing, or Logistics Execution.
Experience within the Salesforce Ecosystem (Agentforce Specialist, Data Cloud, Apex, Flow, or Headless architectures).
Hands-on experience with cloud data platforms (Snowflake, Databricks, BigQuery).
