Job Description

We are seeking a Senior Salesforce / Agentforce AI Integration Architect to support the design and scaling of enterprise automation and AI-enabled integration capabilities. This role will focus on connecting internal AI-driven systems, data platform services, and Salesforce Agentforce environments through secure, scalable, and well-governed architecture patterns. The ideal candidate brings deep Salesforce integration and customization experience, strong enterprise systems architecture skills, and practical understanding of LLM-based workflows, agent orchestration, and AI platform integration. Enterprise experience strongly preferred. Key Responsibilities - Architect end-to-end integration designs connecting internal AI systems, data services, and Salesforce Agentforce environments. - Evaluate and recommend integration patterns across traditional APIs, Model Context Protocol, Agent-to-Agent approaches, and event-driven architectures. - Design scalable, secure, and maintainable distributed systems that support autonomous workflows and enterprise automation. - Define how autonomous systems interact safely and efficiently across cloud platforms, data services, and Salesforce environments. - Wrap complex backend processes into agentic tools using Invocable Apex methods, advanced Salesforce Flows, and custom prompt templates. - Design modular agent structures that avoid overloaded reasoning engines and support delegation across specialized autonomous agents. - Establish API contracts, semantic endpoint definitions, trust filters, authentication boundaries, and data exposure guardrails. - Collaborate with engineering, data, Salesforce administration, platform architecture, and security stakeholders. - Author Architectural Decision Records that map high-level requirements to technical constraints, trade-offs, and design decisions.

Qualifications

Must-Have Skills - Strong experience with enterprise integrations and system architecture. - Deep experience integrating systems with Salesforce. - Strong experience with Apex methods, advanced Salesforce Flows, and custom prompt templates. - Experience designing and implementing APIs, including REST, gRPC, and event-driven architectures. - Experience with Salesforce APIs, connectors, and integration patterns. - Solid understanding of AI and LLM concepts, including prompt engineering, context management, context windows, and token conservation. - Experience with multi-step AI workflows, agent orchestration, and autonomous routing concepts. - Experience designing scalable and secure distributed systems. - Understanding of security, authentication, data governance, trust boundaries, and data exposure controls. - Experience documenting architecture decisions, technical constraints, and trade-offs. - Strong collaboration skills across engineering, data, platform, Salesforce, and security teams.

Nice-to-Have

Skills - Experience with Model Context Protocol. - Experience with Agent-to-Agent integrations. - Experience with MuleSoft or middleware platforms. - Experience building or managing autonomous AI agents or micro-agent systems. - Familiarity with Salesforce Agentforce. - Experience with semantic tool discovery or AI-native integrations. - Knowledge of Salesforce Bulk APIs and Salesforce Connect. - Experience working in large-scale enterprise AI environments. Additional Information Required Tools & Platforms - Salesforce - Salesforce Agentforce - Invocable Apex - Salesforce Flows - Custom prompt templates - Salesforce APIs and connectors - REST APIs - gRPC - Event-driven architecture - Salesforce Pub/Sub API - LLM and agentic AI workflow concepts - Architectural Decision Records Location, Time & Engagement - Remote contract role. - Open to candidates in the United States, LATAM, EMEA, and APAC. - Must be able to collaborate effectively with U.S.-based stakeholders and cross-functional teams. - Full-time engagement, 40 hours per week. - Expected engagement through March 31, 2027.