About this role
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.