Own the AI lifecycle for your customer portfolio prompt optimization, guardrail management, drift monitoring, output tuning, and configuration governance from go-live through renewal.
Maintain a configuration baseline registry for each customer, tracking deployed versions, change history, and performance against design intent.
Lead Quarterly Technical Success Reviews, delivering ROI analysis, drift findings, upgrade impact assessments, and optimization roadmaps to customer stakeholders.
Serve as the primary AI advisor for your portfolio, translating Agentforce capabilities into measurable business outcomes and guiding customers on what is achievable within their existing architecture.
Leverage deep Salesforce platform knowledge Apex, Flows, LWC, data cloud/data 360, and custom configurations to diagnose issues and assess enhancement feasibility directly within customer environments.
Own the AI lifecycle for your customer portfolio prompt optimization, guardrail management, drift monitoring, output tuning, and configuration governance from go-live through renewal.
Own production deployment approval for all post-go-live configuration changes, ensuring no undocumented changes enter production environments.
Provide guidance, troubleshooting, and support for general configuration questions and issues
Required Qualifications
3+ years in a technical customer-facing role such as Customer Success, Solutions Engineering, or Technical Account Management.
Hands-on Salesforce platform expertise including Apex code, Flows, Lightning Web Components (LWC), custom buttons, page layouts, validation rules, and declarative and programmatic customizations.
Demonstrated experience configuring and troubleshooting Salesforce automation, including Screen Flows, Record-Triggered Flows, and Apex triggers in production environments.
Working knowledge of Salesforce data model, object relationships, and integration patterns including REST/SOAP APIs and Platform Events.
Demonstrated experience with prompt engineering, LLM behavior, or AI output optimization in a production environment.
Ability to translate complex AI behavior and technical Salesforce configuration into clear business language for non-technical stakeholders.
Strong documentation discipline with experience producing technical specifications, runbooks, or operational guides.
Bachelor's degree in information systems, computer science, business, or a related field, or equivalent demonstrated experience.
Preferred Qualifications
Salesforce Agentforce experience or Salesforce AI Associate / AI Specialist certification, or active pursuit.
Experience with Data Cloud
Salesforce Administrator or Platform Developer I certification or active pursuit.
Experience with Salesforce Data Cloud including schema design, data streams, or unified profiles.
Proficiency with Salesforce debugging tools including Developer Console, debug logs, and flow error handling.
Familiarity with change management frameworks or enterprise AI governance models.
Background in B2B SaaS with enterprise accounts and SOW-based delivery cycles.
Exposure to AI lifecycle management including drift monitoring, guardrail design, and model version governance.
