Enterprise AI Implementation Engineer — Salesforce Agentforce, Agentic AI & LLMs
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level, metro role but niche Agentforce/LLM specialization reduces applicant density.
Role requires niche Salesforce Agentforce and enterprise GenAI experience, limiting cross-industry transferability.
Mandatory 5+ years, 3+ GenAI experience and specific Salesforce Agentforce and security skills create strict filters.
Job Description
Structured overview of role & requirementsAbout This Role
Design and deliver production-grade Agentic AI, LLM, and RAG solutions integrated with Salesforce Agentforce for global enterprises.
Build and integrate Salesforce Agentforce agents, actions, prompts, and guardrails with Service Cloud, Sales Cloud, and Data Cloud.
Own CI/CD, security controls, cost optimization, and knowledge transfer to customer-operated teams.
Minimum Requirements
5+ years enterprise engineering experience with at least 3 years delivering AI/ML or GenAI production systems.
Hands-on experience with Salesforce Agentforce, Einstein AI, Prompt Builder, Flows, Apex, and at least one major cloud AI platform.
Strong knowledge of security, PII handling, model risk, and enterprise data governance.
Location requirement: Hyderabad, India.
Ideal Candidate Profile
Experienced in end-to-end AI solution deployment, especially within Salesforce ecosystems.
Skilled in operational ownership covering CI/CD, security, and cost management for enterprise AI products.
Comfortable working with complex CRM and enterprise data architectures and governance frameworks.