Forward Deployed Engineer_Salesforce Agentforce / Consumer Lending

Job Description

Must Have Technical/Functional Skills

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We are seeking a hands-on Forward Deployed Engineer (FDE) to design, develop, and deploy agentic AI solutions for consumer lending. Working closely with business stakeholders and delivery teams, the FDE will transform operational challenges into production solutions that improve efficiency, quality, and member experience across front, middle, and back-office processes.

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• Strong hands-on experience with Salesforce Agentforce, including agent configuration, agent actions, instructions, prompt templates, workflows, and orchestration.

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• Expertise in Salesforce Development using Apex, Lightning Web Components (LWC), Salesforce Flow, SOQL, and Platform Events.

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• Experience with Prompt Engineering, Generative AI, Agentic AI architectures, Retrieval-Augmented Generation (RAG), tool invocation, grounding, and AI response evaluation.

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• Proficiency in designing and consuming REST/SOAP APIs and integrating Salesforce with enterprise applications.

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• Hands-on experience with MuleSoft or similar integration platforms for connecting CRM, lending, and core banking systems.

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• Strong understanding of Salesforce Financial Services Cloud (FSC) and lending-related business processes.

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• Experience implementing secure AI solutions, including role-based access control, auditability, data privacy, and governance controls.

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• Knowledge of CI/CD pipelines, Git-based source control, DevOps processes, Salesforce deployment frameworks, and release management.

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• Experience with automated testing, integration testing, performance testing, and AI validation frameworks.

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• Ability to analyze business processes and translate operational requirements into scalable AI-driven solutions.

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• Experience troubleshooting complex production issues across Salesforce, integrations, AI services, and enterprise platforms.

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• Understanding of enterprise architecture principles, API-led connectivity, system design, and cloud-native application development.

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• Strong knowledge of consumer lending lifecycle processes, including application intake, underwriting support, document collection, verification, servicing, exception processing, and member communications.

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• Experience working with structured and unstructured enterprise data sources to support AI-driven decision-making and agent responses.

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• Familiarity with AI governance, model evaluation, prompt security, hallucination mitigation, human-in-the-loop controls, and responsible AI practices.

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• Ability to collaborate effectively with business stakeholders, architects, security teams, QA teams, and product owners in an Agile delivery environment.

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Roles & Responsibilities

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• Understand lending workflows: Partner with lending operations and Business Analysts to identify manual activities, map exceptions, and translate requirements into implementable AI solutions.

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· Prototype and validate: Build working prototypes, demonstrate solutions to business users, incorporate feedback, and establish measurable acceptance criteria.

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· Develop Agentforce solutions: Configure agent instructions, actions, prompts, and workflows; develop supporting components using Apex, Lightning Web Components, and Salesforce Flow.

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· Integrate enterprise systems: Connect agents with lending platforms, document repositories, core banking systems, and external services through MuleSoft and APIs.

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· Enable reliable AI execution: Ground responses in approved enterprise data, validate agent outputs, and implement error handling, human handoffs, and approval checkpoints.

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· Deliver secure solutions: Implement access controls, protection of sensitive member information, and audit trails in partnership with architecture and security teams.

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· Test and improve: Work with QA to evaluate response accuracy, action correctness, exception scenarios, prompt injection, integration failures, and performance.

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· Own engineering delivery: Drive development, defect resolution, deployment, and post-launch stabilization. Prepare technical evidence for architecture, security, testing, and release tollgates, coordinating approvals with designated owners.

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· Measure and scale: Monitor agent performance, processing time, manual effort, adoption, and operating cost. Create reusable components, documentation, and support runbooks.