[Remote] Junior Salesforce AI Engineer

Note: The job is a remote job and is open to candidates in USA. iFIT is a company focused on creating a holistic health and fitness platform that integrates various elements of health into an interactive experience. They are seeking a Junior Salesforce AI Engineer to configure and optimize their Salesforce platform with a focus on Einstein AI and CPQ capabilities, driving adoption of AI tools to enhance sales performance and accuracy.

Responsibilities

• Drive adoption of Salesforce Einstein AI and CPQ tools to improve visibility into quoting, pricing, and sales performance, delivering actionable insights through opportunity scoring, lead prioritization, and CPQ reporting dashboards
• Contribute to revenue and contribution margin growth by optimizing CPQ pricing rules, discount guardrails, and quote accuracy, while surfacing pricing trends through Einstein-driven analysis and structured reporting
• Partner cross-functionally with Sales, Revenue Operations, and the Salesforce Admin team to align product catalog configuration and availability with demand, supporting smooth product transitions and business continuity
• Improve forecast accuracy by enhancing data visibility through Einstein Opportunity Scoring, Activity Capture, and structured reporting, building the data foundation required for advanced AI-driven planning in future phases
• Identify and implement Inside Sales efficiency gains through streamlined CPQ workflows, Flow-based automation, and Einstein-powered prioritization, reducing manual effort and improving rep productivity
• Configure and maintain Einstein Lead Scoring and Opportunity Scoring, including model training data hygiene, threshold calibration, and rep adoption enablement
• Set up and iterate on Einstein Next Best Action recommendations to guide rep behavior at key moments in the sales cycle
• Configure Einstein Activity Capture to ensure email and calendar data flows accurately into Salesforce, supporting rep productivity and downstream AI model quality
• Monitor and tune Case Classification performance within Service Cloud based on accuracy feedback from service teams
• Build and maintain CPQ pricing rules, discount schedules, and product catalog configurations to support accurate, efficient quoting for Inside Sales
• Develop and optimize quote templates and CPQ output documents to reduce quote generation time and improve the buyer experience
• Partner with Revenue Operations to identify and resolve CPQ workflow bottlenecks, including approval processes, product bundles, and subscription management
• Maintain CPQ data integrity, keeping product catalog, price books, and rules synchronized with current business needs and product transitions
• Write and maintain Apex triggers and Lightning Web Components (LWC) that surface Einstein AI outputs within sales workflows, including scoring visibility, action recommendations, and CPQ integrations
• Build and manage Salesforce Flow automations that orchestrate Einstein-driven actions, routing logic, and sales process steps without custom code where possible
• Collaborate with the Salesforce Admin team within the established Gearset DevOps pipeline, working in sandbox, following promotion workflows, and maintaining clean deployment practices
• Develop dashboards and reports that make Einstein AI outputs actionable, surfacing scoring trends, activity patterns, quote performance, and forecasting signals for Sales leadership
• Maintain data quality standards within Sales Cloud to ensure Einstein models have clean, consistent inputs, including field hygiene, record completeness, and deduplication practices
• Document AI model configurations, scoring thresholds, and automation logic to support handoffs, onboarding, and iterative improvement over time
• Perform unit testing and UAT for Einstein-driven workflows and CPQ changes, verifying model accuracy and preventing unintended behavior before production deployment
• Monitor deployed AI features post-launch for scoring drift, edge cases, or adoption gaps, and iterate based on rep feedback and data quality signals

Skills

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience
• 1–2 years of hands-on Salesforce development and administration across Sales Cloud and Service Cloud, with direct experience configuring Einstein AI features and Salesforce CPQ
• Proficiency in Apex, SOQL, Salesforce Flow, Lightning Web Components (LWC), and Salesforce APIs
• Working knowledge of Salesforce CPQ including pricing rules, product catalogs, quote templates, and approval workflows
• Demonstrated experience with Einstein Lead Scoring, Opportunity Scoring, Activity Capture, and Next Best Action configuration
• Salesforce Administrator certification required
• Authorized to work in the United States without sponsorship
• Salesforce Certified AI Associate
• Salesforce Platform Developer I or Platform App Builder certification
• Salesforce CPQ Specialist certification
• Experience with Gearset or equivalent Salesforce DevOps tooling and sandbox management
• Familiarity with foundational AI/ML concepts including model training inputs, scoring thresholds, and data quality for AI in the context of CRM platforms
• Experience building Salesforce dashboards and reports for revenue performance and sales analytics use cases
• Understanding of Agentforce architecture, Einstein Copilot, and Prompt Builder template configuration
• Experience with Salesforce Data Cloud including data streams, data model mapping, and identity resolution
• Salesforce Data Cloud or AI Specialist certifications
• Prompt engineering experience and understanding of responsible AI practices including hallucination prevention and grounding strategies

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