Senior Salesforce / Agentforce, AI Platform Integration Architect

Role OverviewTeam is seeking a highly skilled and strategic AI Platform Integration Architect to drive the next generation of our enterprise automation ecosystem. In this role, you will bridge the gap between our internal data architectures and Salesforce s advanced agentic capabilities. A core focus of this position is the evolution and enterprise scaling of an autonomous AI co-worker built and operated internally.Must-Have SkillsAgentic AI ArchitectureSolid understanding of Large Language Model (LLM) orchestration, prompt engineering, context windows, and token conservationExperience designing autonomous routing systems that leverage semantic understanding to execute multi-step tool callsEnterprise IntegrationProven expertise in high-scale data synchronization patternsMasterful command of REST, gRPC, and event-driven architectures (e.g., Salesforce Pub/Sub API) to coordinate distributed cloud systemsSalesforce Customization Deep familiarity with wrapping complex backend processes into agentic tools via:Invocable Apex methodsAdvanced Salesforce FlowsCustom prompt templatesArchitectural GovernanceExperience authoring comprehensive Architectural Decision Records (ADRs) that clearly map High-Level Requirements (HLRs) against technical constraints and explicit trade-offsMust-Have Skills (Additional) Strong experience with enterprise integrations and system architectureStrong Apex methods, advanced Salesforce Flows, and custom prompt templatesExperience with APIs (REST, gRPC, event-driven architectures)Experience integrating systems with SalesforceKnowledge of AI/LLM concepts such as:Prompt engineeringContext managementMulti-step AI workflowsAgent orchestrationExperience designing scalable and secure distributed systemsExperience with Salesforce tools such as:Salesforce FlowsAPIs and connectorsUnderstanding of security, authentication, and data governanceExperience documenting architecture decisions and technical trade-offsStrong collaboration skills across engineering, data, and security teamsNice-to-Have (Preferred)Experience with Model Context Protocol (MCP)Experience with Agent-to-Agent (A2A) integrationsExperience with MuleSoft or middleware platformsExperience building or managing autonomous AI agents or micro-agent systemsFamiliarity with Salesforce AgentforceExperience with semantic tool discovery or AI-native integrationsKnowledge of Bulk APIs and Salesforce ConnectExperience working in large-scale enterprise AI environmentsKey ResponsibilitiesSystem Orchestration & BlueprintingArchitect end-to-end integration designs connecting Indeed s internal AI co-worker and related data platform services to Salesforce Agentforce environmentsPattern Optimization & Decisioning Apply rigorous architectural frameworks to choose the correct integration pattern (Traditional APIs, Model Context Protocol, or Agent-to-Agent) based on:Transaction volumeReasoning overheadLatency boundariesData sensitivityAgent Specialization ManagementDesign modular agent structures to avoid monolithic, overloaded reasoning enginesEnforce governance limits (e.g., maintaining under 10 topics per agent) by delegating complex tasks across specialized autonomous micro-agentsCross-Functional CollaborationWork directly with Data Engineers, Salesforce Administrators, Core Platform Architects, and Security OperationsMaintain unified API contracts and clean semantic understanding across all endpointsSecurity and Trust GovernanceEstablish explicit trust filters, secure authentication boundaries, and data exposure guardrailsProtect sensitive corporate assets while maintaining fluid agent execution