Forward Deployed Engineer, Salesforce

• 3+ years of software engineering or technical delivery experience, with at least one production AI, data engineering, or enterprise integration system deployed to production
• High proficiency in at least one modern language: Python, JavaScript/TypeScript, Java, or Apex
• 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
• Strong executive presence - ability to whiteboard architecture with enterprise CTOs and VPs while writing production code alongside lead architects
• Familiarity with automation platforms (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 (Workday, Coupa, Jira, Slack, major warehouse or transportation management systems) and deployment infrastructure (Kafka, AWS EventBridge, Azure Service Bus, GitHub, Docker, Kubernetes, Terraform)
• 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)
• Understanding of enterprise security and governance: Identity and access management, OAuth, data privacy, audit logging, permissioning, and secure tool execution
• Willingness to travel 25-30% for on-site deployment with key enterprise accounts

Desirable

• As a Forward Deployed Engineer (FDE) focusing on Agentforce Operations, you are a hands-on Technical Builder who designs, constructs, and deploys enterprise-grade agentic AI solutions directly inside customer environments
• AFO powers the multi-agent orchestration layer, transforming messy operational workflows, unstructured data (emails, PDFs, spec sheets), and legacy ERP logs into autonomous execution engines with humans in the loop
• Operating in an agile deployment pod alongside a Deployment Strategist and Specialized AI Engineers, 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
• Workflow & Multi-Agent Orchestration: Build, configure, and optimize complex operational workflows using AFO, 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