Senior Specialist - Software Engineering

Salesforce AI Engineer / Agentforce Engineer

Job Summary

We are seeking an experienced Salesforce AI Engineer to design, build, integrate, and operationalize AI-driven solutions within the Salesforce ecosystem. The ideal candidate will combine strong Salesforce development and integration expertise with hands-on experience in Generative AI, Agentforce, Data Cloud, RAG, Python, and AI/ML technologies.

This role will focus on building secure, scalable, and production-ready AI capabilities that integrate directly with Salesforce business processes.

Key Responsibilities

AI & Generative AI

• Design and implement Generative AI, Predictive AI, Retrieval-Augmented Generation (RAG), natural language classification, summarization, recommendation, and intelligent automation solutions.
• Build reusable prompt templates, grounding strategies, evaluation datasets, guardrails, fallback mechanisms, and human-in-the-loop controls.
• Develop AI services and APIs using Python and common AI/ML frameworks following enterprise engineering standards.
• Evaluate AI solutions using metrics such as accuracy, relevance, groundedness, safety, latency, reliability, and cost.
• Implement responsible AI practices related to privacy, security, access controls, audit logging, prompt injection prevention, and sensitive-data protection.

Salesforce AI & Agentforce

• Design and implement AI capabilities using:
  • Salesforce Agentforce
  • Salesforce Data Cloud
  • Prompt Builder
  • Model Builder
  • Einstein AI capabilities
• Configure Agentforce topics, actions, instructions, grounding sources, orchestration flows, and escalation paths aligned with business outcomes.
• Integrate Salesforce with external AI services, LLMs, and model endpoints using secure authentication and API patterns.

Salesforce Development & Integration

• Design, develop, and extend Salesforce solutions using:
  • Apex
  • Lightning Web Components (LWC)
  • Visualforce
  • Salesforce Flow
  • SOQL / SOSL
  • REST / SOAP APIs
  • Streaming APIs
  • Platform Events
  • Named Credentials
• Develop secure, scalable integrations between Salesforce, enterprise applications, and external AI services.
• Apply Salesforce development best practices including governor limit awareness, bulk-safe development, automated testing, and secure coding standards.

Security & DevOps

• Implement Salesforce security controls including:
  • Sharing models
  • Permission Sets
  • Field-Level Security
  • Access controls
  • Auditability
• Use Git-based development, code reviews, automated testing, CI/CD pipelines, environment management, and production support practices.

Required Qualifications

• Strong hands-on experience with Salesforce development and integration.
• Strong experience with Apex, LWC, Flow, SOQL/SOSL, and Salesforce APIs.
• Hands-on experience with Salesforce Agentforce and/or Salesforce AI technologies.
• Experience with Data Cloud, Prompt Builder, Model Builder, or Einstein.
• Experience developing applications or services using Python.
• Understanding of Generative AI, LLMs, RAG, prompt engineering, grounding, AI evaluation, and guardrails.
• Experience integrating external AI/ML services or model endpoints with enterprise applications.
• Understanding of Responsible AI, data privacy, security, access controls, and AI safety principles.
• Experience with Git, CI/CD, automated testing, and enterprise software development practices.
• Strong analytical, troubleshooting, documentation, and stakeholder communication skills.

Preferred Qualifications

• Experience implementing production Agentforce solutions.
• Experience connecting Data Cloud data with AI agents or Generative AI applications.
• Experience designing RAG architectures and enterprise knowledge-grounding solutions.
• Familiarity with major AI/LLM platforms and APIs.
• Salesforce certifications such as Platform Developer I/II, AI Associate, AI Specialist, or relevant Salesforce architecture credentials.