Lead Salesforce Agentforce AI Developer

EPAM Systems Inc

United States

Remote

USD 150,000 - 210,000

Full time

3 days ago
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Job summary

EPAM Systems seeks a Lead Salesforce Developer to steer the design and development of Agentforce Generative AI agents. You will lead hands-on efforts, optimize the Salesforce platform, and drive AI‑driven solutions ensuring scalability and strong business impact.

You will collaborate with architects and engineers to deliver robust AI agent implementations, manage priorities, and refine implementations through performance tuning and refactoring.

Qualifications

  • 6+ years of hands-on experience in Salesforce development.
  • At least 1 year of relevant leadership experience.
  • Proficiency in implementing AI agents using Salesforce Agentforce.
  • Experience configuring agent reasoning, guardrails, action frameworks, and workflows.
  • Knowledge of data modeling, integration with third-party systems, and performance tuning.

Responsibilities

  • Collaborate with architects and team members to design and implement AI agents using Salesforce Agentforce.
  • Lead design and development of AI agents with scalable, optimized solutions.
  • Gather requirements and report progress to stakeholders.
  • Conduct technical research and analysis to propose optimized solutions.
  • Provide support during maintenance, improving performance and adding enhancements.

Skills

Leadership
AI agent design
Salesforce Agentforce
Apex
Lightning Web Components
Flow
Data modeling
Performance optimization
System integration
Stakeholder communication

Tools

Salesforce Agentforce
Apex
Lightning Web Components
Flow
REST/SOAP APIs
Salesforce Platform

Job description

EPAM Systems seeks a Lead Salesforce Developer to steer the design and development of Agentforce Generative AI agents. You will lead hands-on efforts, optimize the Salesforce platform, and drive AI‑driven solutions ensuring scalability and strong business impact.

You will collaborate with architects and engineers to deliver robust AI agent implementations, manage priorities, and refine implementations through performance tuning and refactoring.

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