Agentforce Operations FDE

Leadout Capital; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Leadout Capital seeks a Forward Deployed Engineer focused on Agentforce Operations. You will design, build, and deploy enterprise-grade agentic AI solutions inside customer environments, bridging AI agents with ERP, data clouds, and enterprise apps.

You’ll work in an agile pod with a Deployment Strategist and Specialized AI Engineers, shipping production code from day one. You will implement agent communication protocols, grounding systems, and API pipelines, using tools like MuleSoft, Docker,

Qualifications

• 3+ years of software engineering or technical delivery experience.
• Proficient in at least one modern language: Python, JavaScript/TypeScript, Java, or Apex.
• Hands-on AI & grounding expertise with LLM orchestration and RAG pipelines.
• API design experience (REST/SOAP/webhooks) and agent protocols (MCP, tool calling).
• Process orchestration and API-led connectivity using MuleSoft or middleware.
• Data modeling, schema design, and asynchronous messaging patterns.
• Executive-level architecture whiteboarding with CTOs/VPs while coding.
• Familiarity with automation platforms (Pega, UiPath, RPA) and other enterprise AI platforms.
• Experience with integrated enterprise apps (Workday, Coupa, Jira, Slack) and deployment infra (Kafka, EventBridge, Service Bus, Docker, Kubernetes, Terraform).
• Knowledge of data governance (Informatica, Collibra) and ops platforms (Manhattan, Blue Yonder, Kinaxis).
• Understanding of enterprise security, IAM, OAuth, data privacy, and auditing.
• Willingness to travel 25-30% for on-site deployment.

Responsibilities

• Build, configure, and deploy complex multi-agent orchestration workflows using AFO.
• Implement agent communication protocols and context sharing standards (MCP).
• Design real-time data grounding systems with RAG and vector databases.
• Develop APIs and integration pipelines to connect AFO/Agentforce to ERP, CRM, and data clouds.
• Leverage Cursor, Claude, and Vibes to move from architecture to production code quickly.
• Ship telemetry, ETL/ELT pipelines, and real-time dashboards for health and outcomes.
• Bridge frontline deployments with Salesforce product/engineering for edge-case feedback.

Skills

Python

JavaScript/TypeScript

Java

Apex

LLM orchestration

RAG pipelines

API design (REST/SOAP/webhooks)

MCP

MuleSoft

Data modeling

Asynchronous integration

Workday/Coupa/Jira/Slack

Docker/Kubernetes

Terraform

AAI observability

Executive communication

Tools

MuleSoft

Docker

Kubernetes

Terraform

Snowflake

Databricks

GraphQL

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.