Agentforce Operations FDE

Leadout Capital; Amsterdam; On-site; EUR 90,000 - 140,000; Full time

Job summary

Leadout Capital is seeking a Forward Deployed Engineer to design, build, and deploy enterprise-grade agentic AI solutions inside customer environments. You will join an agile deployment pod and connect advanced AI agents to the broader enterprise tech stack.

You will implement real-time grounding systems, multi-agent communication, and API integrations with core ERPs, data platforms, and cloud services. Travel 25-30% for on-site deployments.

Qualifications

• 3+ years of software engineering or technical delivery experience with at least one production AI or enterprise integration deployment.
• Proficiency in at least one modern language: Python, JavaScript/TypeScript, Java, or Apex.
• Hands-on AI and grounding expertise across LLM orchestration, prompts, and RAG pipelines.

Responsibilities

• Build, configure, and deploy multi-agent orchestration workflows inside customer environments.
• Implement agent communication protocols and MCP to govern context sharing and tool execution.
• Architect real-time data grounding systems using vector databases and knowledge bases.
• Develop and maintain APIs (REST, GraphQL, webhooks) and integration pipelines to connect AFO/Agentforce with enterprise systems.
• Create and maintain telemetry dashboards to monitor agent performance and health.
• Collaborate with Salesforce product/engineering teams to feed edge cases into roadmaps.

Skills

Python

JavaScript/TypeScript

Java

Apex

LLM orchestration

Prompt tuning

RAG pipelines

Vector search indexes

Knowledge bases

REST

GraphQL

Webhooks

MuleSoft

API design

Data modeling

Async messaging

Kafka

Cloud platforms

Tools

MuleSoft

REST

GraphQL

Webhooks

Kafka

AWS EventBridge

Azure Service Bus

Docker

Kubernetes

Terraform

Job description

Forward Deployed Engineer — Agentforce Orchestration

About the Role

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.

What You'll Actually Be Building

• 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.

Required Qualifications

• 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.

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).

• Proven ability to create reusable accelerators, reference architectures, connectors, and implementation playbooks from customer deployments.