FDE

We are looking for a highly hands-on Salesforce Forward Deployed Engineer (FDE) who can work directly with customers to solve complex business problems using Salesforce, AI, and modern engineering technologies. The FDE will operate at the intersection of business process, solution architecture, software engineering, AI, and customer delivery, rapidly translating business problems into production-ready solutions.

This role requires someone who can go beyond traditional Salesforce configuration and development. The ideal candidate will be comfortable working with ambiguous requirements, conducting technical discovery, building prototypes, writing production-quality code, integrating enterprise systems, and deploying AI-powered solutions using Agentforce, Data Cloud, Claudeforce, Salesforce Platform, APIs, and Generative AI technologies.

The FDE will work closely with customer executives, product owners, architects, engineering teams, and delivery leaders throughout the solution lifecycle from discovery and experimentation through production deployment and adoption.

Key Responsibilities

• Partner directly with customers to understand complex business problems and translate them into scalable technical solutions.
• Lead technical discovery sessions and translate ambiguous business requirements into actionable solution designs.
• Design and build Agentforce-based autonomous and assistive agents using topics, instructions, actions, prompts, Flow, Apex, APIs, and enterprise data.
• Develop Salesforce applications using Apex, Lightning Web Components (LWC), Flow, SOQL, REST APIs, Platform Events, and other Salesforce platform capabilities.
• Design AI-powered workflows grounded in Salesforce, Data Cloud, Knowledge, and external enterprise data.
• Build and configure Data Cloud solutions, including data ingestion, harmonization, identity resolution, calculated insights, segmentation, and activation.
• Integrate Salesforce with enterprise applications and AI platforms through APIs, MuleSoft, event-driven patterns, and custom integration services.
• Build prototypes and proof-of-concepts quickly, validate them with customers, and evolve successful prototypes into production-grade solutions.
• Develop supporting services and utilities using technologies such as Python, JavaScript/TypeScript, APIs, and cloud-native services where Salesforce-native capabilities alone are insufficient.
• Apply Generative AI and LLM capabilities to use cases such as intelligent search, summarization, classification, recommendations, workflow automation, and autonomous task execution.
• Design appropriate human-in-the-loop controls, guardrails, permissions, observability, auditability, and responsible AI mechanisms.
• Troubleshoot complex application, integration, data, and AI issues across Salesforce and connected platforms.
• Collaborate with Salesforce architects, developers, data engineers, AI engineers, product teams, and customer engineering organizations.
• Establish reusable engineering patterns and accelerators that can be leveraged across multiple customer engagements.
• Provide technical leadership from initial discovery through architecture, development, testing, deployment, stabilization, and handover.

Required Experience

• Strong hands-on experience with the Salesforce Platform, including Apex, LWC, Flow, SOQL, security, data model, and integration capabilities.
• Experience designing or implementing solutions using Salesforce Agentforce and/or Generative AI capabilities.
• Strong understanding of Salesforce integration patterns, REST/SOAP APIs, event-driven architecture, authentication, and enterprise integration.
• Experience writing production-quality code using Apex and at least one general-purpose language such as Python or JavaScript/TypeScript.
• Understanding of LLM concepts including prompting, grounding, retrieval/RAG, tool/action execution, structured outputs, evaluation, and AI guardrails.
• Experience taking solutions from prototype or POC through enterprise production deployment.
• Strong understanding of enterprise architecture, security, scalability, performance, and software engineering practices.
• Ability to independently diagnose technical issues across applications, integrations, APIs, data, and AI components.
• Experience in enterprise domains such as Sales, Service, CPQ/Revenue, Healthcare & Life Sciences, Financial Services, Telecom, or Commerce is beneficial.

Customer-Facing Expectations

A Salesforce FDE is expected to be significantly more customer-facing than a traditional developer. The individual should be comfortable working directly with customer business and technology stakeholders, including senior leadership.

The FDE should be able to take an ambiguous business problem, structure it into solvable components, identify the appropriate Salesforce and AI capabilities, develop a working solution, demonstrate it to stakeholders, incorporate feedback, and drive the solution toward production.

Strong communication skills are therefore essential. Candidates should be able to explain sophisticated AI and architecture concepts in practical business terms while also engaging deeply with architects and engineers.

Engineering Mindset

We are specifically looking for builders rather than purely advisory architects. The successful candidate should be comfortable opening an IDE, analyzing APIs and data, writing code, configuring Salesforce, developing an agent, debugging integrations, and demonstrating a working solution directly to a customer.

The FDE should demonstrate a bias toward rapid experimentation while maintaining enterprise engineering standards for production solutions.

Required Skills-Sets

Salesforce Platform

• Salesforce Sales Cloud, CPQ, Service Cloud, Experience Cloud, and Platform Development.
• Expertise in Apex, Lightning Web Components (LWC), SOQL, SOSL, platform events, and Salesforce APIs.
• Salesforce DX and debugging practices.AI & Agentic Capabilities
• Salesforce Agentforce, Einstein AI, Einstein Copilot, Prompt Builder, Model Builder, AI Studio
• Experience with OpenAI, Anthropic Claude, AWS Bedrock, Google Gemini/Vertex AI, or similar AI platforms is preferred.
• Data Cloud - Data Cloud architecture, Data Streams, Data Lake Objects (DLOs), Data Model Objects (DMOs), identity resolution, calculated insights, segmentation, and activation.Integration & Data
• REST/SOAP APIs
• MuleSoft, Azure Integration Services, or similar enterprise integration platforms
• Event-driven architecture
• Data governance and metadata managementAI & Modern Engineering
• Retrieval-Augmented Generation (RAG)
• Large Language Models (LLMs)
• Vector Search concepts
• Prompt Engineering
• AI Evaluation Frameworks
• Agent Orchestration
• Conversational AIDevOps & Security
• GitHub
• Azure DevOps
• Salesforce DevOps Center
• CI/CD implementation
• Test Automation
• OWASP and Salesforce Security Best Practices

Preferred Certifications

Relevant Salesforce certifications are preferred, particularly credentials covering:

• Salesforce Platform development
• Application/System Architecture
• Agentforce
• Data Cloud
• Integration Architecture
• Salesforce Forward Deployed Engineering
• Claude Architect