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Salesforce

Builds cloud software for customer relationships

Agentforce Operations Forward Deployed Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • At least 3 years of software engineering or technical delivery experience, including at least one production AI, data engineering, or enterprise integration system deployed to production.
  • High proficiency in at least one of Python, JavaScript/TypeScript, Java, or Apex.
  • Deep experience with large language model orchestration, prompt tuning, and building retrieval-augmented generation pipelines, vector search indexes, and knowledge-base retrievers for enterprise data.
  • Practical experience with API design, including REST, SOAP, or webhooks, and modern agent protocols such as Model Context Protocol, tool calling, or event-driven messaging architectures.
  • Expertise in process orchestration and API-led connectivity using MuleSoft or custom middleware to connect AI agents with legacy ERP systems.
  • Understanding of data modeling, schema design, and asynchronous message integration patterns.
  • Ability to whiteboard architecture with enterprise CTOs and VPs while writing production code alongside lead architects.
  • Familiarity with automation platforms such as Pega, UiPath, Automation Anywhere, ServiceNow, Appian, or Microsoft Power Platform, and enterprise AI and agent platforms such as Microsoft Copilot Studio, Google Vertex AI, AWS Bedrock, IBM watsonx, Palantir AIP, or ServiceNow AI Agents.
  • Experience with integrated enterprise applications such as Workday, Coupa, Jira, Slack, or warehouse and transportation management systems, and deployment infrastructure such as Kafka, AWS EventBridge, Azure Service Bus, GitHub, Docker, Kubernetes, or Terraform.
  • Knowledge of data governance and master data systems such as Informatica, Collibra, SAP MDG, or Reltio, and operational execution platforms such as Manhattan Associates, Blue Yonder, Kinaxis, or Oracle transportation management.
  • Understanding of enterprise security and governance, including 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.

Responsibilities

  • Build, configure, and optimize operational workflows using Agentforce Operations, including agent reasoning, tool-calling logic, and conditional execution loops.
  • Implement agent-to-agent communication standards and the Model Context Protocol to govern context sharing, task hand-offs, and tool execution across specialized AI agents.
  • Architect, build, and maintain real-time data-grounding infrastructure using retrieval-augmented generation, vector databases, search indexes, and knowledge bases.
  • Develop and maintain custom APIs and integration pipelines connecting Agentforce Operations to Salesforce Data Cloud, cloud warehouses such as Snowflake and Databricks, and ERP systems such as SAP, Oracle, and NetSuite through MuleSoft or custom middleware.
  • Use AI tools such as Cursor, Claude, and Vibes in the developer workflow to create deployable code.
  • Model data, ship ETL/ELT pipelines, and build real-time agent-performance dashboards to track execution health, fallback triggers, and business outcomes.
  • Connect frontline customer deployments with Salesforce product and engineering teams, relaying edge cases and gaps to inform platform feature roadmaps.
  • Design, construct, and deploy enterprise-grade agentic AI solutions directly in customer environments.
  • 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.

Desired Qualifications

  • Specific domain expertise in supply chain, manufacturing, or logistics execution.
  • Experience within the Salesforce ecosystem, including Agentforce Specialist, Data Cloud, Apex, Flow, or headless architectures.
  • Hands-on experience with cloud data platforms such as Snowflake, Databricks, or BigQuery.
  • Ability to create reusable accelerators, reference architectures, connectors, and implementation playbooks from customer deployments.

About the Company

Salesforce

Builds cloud software for customer relationships

Salesforce sells cloud software that helps businesses manage sales leads, customer service, marketing, and online commerce from shared customer records. Its flagship Sales Cloud tracks accounts and deals, while Service Cloud organizes support cases and Agentforce builds AI assistants that act on company data. Teams access these tools through a browser and connect outside apps and data sources, with Slack for work messages and Tableau for visual analysis. Salesforce earns most of its revenue from software subscriptions and support, with professional services for implementation and training. Marc Benioff co-founded Salesforce in 1999, and its headquarters are in San Francisco, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Francisco, CA
Founded
1999

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