Design, configure, and iterate on Agentforce agents for Sales use cases including account briefs, proposal support, and next-best-action recommendations
Develop and maintain Salesforce Flow automations that reduce manual handoffs, enforce lifecycle rules, and surface timely signals to reps and managers
Prototype rapid AI and automation proofs-of-concept for stakeholder review, with a target turnaround of one to three days per prototype
Support third-party implementation partner(s) on AI-adjacent implementation decisions, acting as the business-side AI authority during platform builds
Produce adoption aids and internal tooling including prompt guides, workflow reference materials, quick-start assistants, and in-platform help content
Evaluate new LLM and agent capabilities continuously and translate them into practical, governed, high-value business improvements
Collaborate with IT on security review, data access governance, and production deployment of all AI-powered workflows
Partner with Sales and Marketing teams in discovery sessions to define automation requirements and validate that shipped solutions match real workflows

3+ years of hands-on experience with Salesforce automation, including Salesforce Flow, Process Builder, or equivalent declarative tools
Demonstrated experience with LLM APIs, prompt engineering, or AI agent frameworks — you have built agents or automated workflows using language models
Proven ability to deliver working prototypes rapidly from a standing start; a portfolio of things you have shipped matters more than certifications
Comfortable working directly and frequently with non-technical commercial stakeholders to define requirements and validate solutions
Strong understanding of B2B commercial workflows: lead lifecycle, opportunity management, pipeline reporting, and proposal processes
Solid grasp of data security and governance principles relevant to AI systems, including prompt injection risks, data access scoping, and audit logging

AI Use Case Developer

Key skills