Note: The job is a remote job and is open to candidates in USA. iFIT is a company dedicated to creating a comprehensive health and fitness platform. They are seeking a Junior Salesforce AI Engineer to enhance their Salesforce platform with a focus on AI and CPQ capabilities, driving sales performance and improving forecasting accuracy through advanced tools and cross-functional collaboration.
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
Company Overview