Senior Salesforce / Agentforce AI Integration Architect
Lifted, an Upwork Company™
Company Description 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.
- 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.
Vacancy posted 7 hours ago
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