About the role
Role Summary We are seeking a Salesforce AI Engineer who understands the Salesforce ecosystem and can identify where AI can create measurable business value across sales, service, operations, and analytics. This role is ideal for someone who can assess a client's existing AI landscape, recommend where Salesforce-native AI capabilities should be used, and help drive implementation in selected high-impact use cases.
What You Will D oAssess business processes and current AI initiatives to identify opportunities where Salesforce AI can complement or outperform standalone AI efforts .Translate business requirements into Salesforce AI use cases, solution options, and implementation roadmaps .Design and implement solutions using Salesforce ecosystem capabilities such as Sales Cloud, Service Cloud, Data Cloud, Flow, Apex, Lightning Web Components, and Agentforce where appropriate .Partner with business and technology stakeholders to prioritize use cases based on impact, feasibility, data readiness, and governance .Support solution delivery end to end, including discovery, prototyping, integration design, testing, deployment, and adoption .Guide responsible AI implementation, including data security, access controls, human-in-the-loop review, and prompt/response quality management
. Required Skil lsStrong understanding of the Salesforce platform, including data model, security, sharing, automation, integrations, and declarative and programmatic developmen t.Hands-on experience with Salesforce implementation or development, including Apex, Lightning Web Components, Flow, APIs, and standard Salesforce object s.Working knowledge of AI/ML concepts, LLM-based applications, and common enterprise AI patterns such as retrieval, grounding, orchestration, and guardrail s.Ability to evaluate business workflows and recommend practical AI use cases that improve productivity, decision-making, customer experience, or operational efficienc y.Experience working with cross-functional teams and converting ambiguous business needs into clear technical solution s.Strong communication skills to explain AI options, trade-offs, risks, and implementation plans to both technical and non-technical stakeholder
s. Preferred Experie nceExposure to Salesforce AI capabilities such as Einstein, Agentforce, copilots, or AI-assisted workflow automati on.Experience in organizations where multiple AI initiatives already exist and a platform-level strategy is needed to reduce duplication and improve reu se.Experience with enterprise systems integration, data platforms, and governance in regulated or complex environmen ts.Prior involvement in proof-of-concepts, pilot implementations, or production rollouts of AI-enabled Salesforce solutio
ns. Example Focus A reasSales productivity: opportunity summarization, next-best action, follow-up automation, and account intellige nce.Service operations: case classification, response drafting, knowledge retrieval, and agent ass ist.Internal efficiency: workflow automation, data enrichment, document summarization, and decision supp ort.Governed AI adoption: selecting Salesforce AI only where it fits the workflow, while integrating with other AI platforms when nee ded.
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About the role
Role Summary We are seeking a Salesforce AI Engineer who understands the Salesforce ecosystem and can identify where AI can create measurable business value across sales, service, operations, and analytics. This role is ideal for someone who can assess a client's existing AI landscape, recommend where Salesforce-native AI capabilities should be used, and help drive implementation in selected high-impact use cases.
What You Will D oAssess business processes and current AI initiatives to identify opportunities where Salesforce AI can complement or outperform standalone AI efforts .Translate business requirements into Salesforce AI use cases, solution options, and implementation roadmaps .Design and implement solutions using Salesforce ecosystem capabilities such as Sales Cloud, Service Cloud, Data Cloud, Flow, Apex, Lightning Web Components, and Agentforce where appropriate .Partner with business and technology stakeholders to prioritize use cases based on impact, feasibility, data readiness, and governance .Support solution delivery end to end, including discovery, prototyping, integration design, testing, deployment, and adoption .Guide responsible AI implementation, including data security, access controls, human-in-the-loop review, and prompt/response quality management
. Required Skil lsStrong understanding of the Salesforce platform, including data model, security, sharing, automation, integrations, and declarative and programmatic developmen t.Hands-on experience with Salesforce implementation or development, including Apex, Lightning Web Components, Flow, APIs, and standard Salesforce object s.Working knowledge of AI/ML concepts, LLM-based applications, and common enterprise AI patterns such as retrieval, grounding, orchestration, and guardrail s.Ability to evaluate business workflows and recommend practical AI use cases that improve productivity, decision-making, customer experience, or operational efficienc y.Experience working with cross-functional teams and converting ambiguous business needs into clear technical solution s.Strong communication skills to explain AI options, trade-offs, risks, and implementation plans to both technical and non-technical stakeholder
s. Preferred Experie nceExposure to Salesforce AI capabilities such as Einstein, Agentforce, copilots, or AI-assisted workflow automati on.Experience in organizations where multiple AI initiatives already exist and a platform-level strategy is needed to reduce duplication and improve reu se.Experience with enterprise systems integration, data platforms, and governance in regulated or complex environmen ts.Prior involvement in proof-of-concepts, pilot implementations, or production rollouts of AI-enabled Salesforce solutio
ns. Example Focus A reasSales productivity: opportunity summarization, next-best action, follow-up automation, and account intellige nce.Service operations: case classification, response drafting, knowledge retrieval, and agent ass ist.Internal efficiency: workflow automation, data enrichment, document summarization, and decision supp ort.Governed AI adoption: selecting Salesforce AI only where it fits the workflow, while integrating with other AI platforms when nee ded.