Salesforce AI Integration Architect ID68517
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AI Summary
Design and build enterprise integrations between internal AI platforms and Salesforce Agentforce to scale autonomous AI workflows. Architect multi-step agentic orchestration patterns and establish security and governance guardrails for AI-native systems.
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Salesforce AI Integration Architect to design and build enterprise integrations between internal AI platforms and Salesforce Agentforce environments, scaling autonomous AI workflows across distributed systems. You will architect multi-step agentic AI orchestration patterns, define integration strategies using REST APIs, gRPC, and event-driven architectures, and establish security and governance guardrails for AI-native enterprise systems. The role requires deep expertise in Salesforce customization, LLM orchestration, and scalable distributed system design.
WHAT YOU WILL DO
- Architect end-to-end integrations between internal AI platforms, enterprise data systems, and Salesforce Agentforce environments;
- Design scalable, secure, and resilient distributed system architectures supporting autonomous AI workflows;
- Define integration strategies leveraging REST APIs, gRPC, event-driven architectures, and Salesforce-native capabilities;
- Design and optimize modular agentic AI systems through specialized micro-agent delegation;
- Build orchestration patterns for multi-step AI workflows, autonomous routing systems, and semantic tool execution;
- Apply best practices around prompt engineering, context management, token conservation, and LLM orchestration;
- Develop and enhance integrations using Salesforce Flows, Invocable Apex methods, APIs, connectors, and custom prompt templates;
- Enable complex backend processes to be exposed as intelligent agentic tools within Salesforce ecosystems;
- Collaborate with cross-functional teams to maintain unified API contracts and semantic consistency across enterprise systems;
- Author architectural decision records documenting technical trade-offs, constraints, and high-level requirements;
- Evaluate and select integration patterns including traditional APIs, Model Context Protocol, and Agent-to-Agent communication models;
- Balance performance, latency, scalability, reasoning overhead, and data sensitivity considerations in architectural decisions;
- Establish authentication boundaries, trust layers, and governance guardrails for AI-enabled enterprise systems;
- Ensure compliance with enterprise security standards, data governance policies, and secure data exposure practices;
- Partner with security and platform teams to maintain reliable and trustworthy autonomous agent execution.
MUST HAVES
- 6+ years of experience designing enterprise integrations and distributed system architectures;
- Hands-on experience integrating systems with Salesforce;
- Deep expertise with Apex methods, advanced Salesforce Flows, custom prompt templates, and Salesforce APIs and connectors;
- Strong experience with REST APIs, gRPC, event-driven architectures, and enterprise synchronization patterns;
- Solid understanding of AI and LLM concepts including prompt engineering, context management, token optimization, multi-step AI workflows, agent orchestration, and semantic routing systems;
- Experience designing scalable and secure distributed systems;
- Strong understanding of authentication, security, trust boundaries, and data governance;
- Experience documenting architecture decisions, trade-offs, and technical strategy;
- Excellent collaboration and communication skills across engineering, platform, data, and security organizations;
- Upper-intermediate English level.
NICE TO HAVES
- Experience with Model Context Protocol (MCP);
- Experience with Agent-to-Agent (A2A) integrations;
- Experience with MuleSoft or enterprise middleware platforms;
- Familiarity with Salesforce Agentforce;
- Experience building or managing autonomous AI agents or micro-agent ecosystems;
- Experience with semantic tool discovery or AI-native integrations;
- Knowledge of Salesforce Bulk APIs and Salesforce Connect;
- Experience operating within large-scale enterprise AI environments.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Salesforce AI Integration Architect to design and build enterprise integrations between internal AI platforms and Salesforce Agentforce environments, scaling autonomous AI workflows across distributed systems. You will architect multi-step agentic AI orchestration patterns, define integration strategies using REST APIs, gRPC, and event-driven architectures, and establish security and governance guardrails for AI-native enterprise systems. The role requires deep expertise in Salesforce customization, LLM orchestration, and scalable distributed system design.
WHAT YOU WILL DO
- Architect end-to-end integrations between internal AI platforms, enterprise data systems, and Salesforce Agentforce environments;
- Design scalable, secure, and resilient distributed system architectures supporting autonomous AI workflows;
- Define integration strategies leveraging REST APIs, gRPC, event-driven architectures, and Salesforce-native capabilities;
- Design and optimize modular agentic AI systems through specialized micro-agent delegation;
- Build orchestration patterns for multi-step AI workflows, autonomous routing systems, and semantic tool execution;
- Apply best practices around prompt engineering, context management, token conservation, and LLM orchestration;
- Develop and enhance integrations using Salesforce Flows, Invocable Apex methods, APIs, connectors, and custom prompt templates;
- Enable complex backend processes to be exposed as intelligent agentic tools within Salesforce ecosystems;
- Collaborate with cross-functional teams to maintain unified API contracts and semantic consistency across enterprise systems;
- Author architectural decision records documenting technical trade-offs, constraints, and high-level requirements;
- Evaluate and select integration patterns including traditional APIs, Model Context Protocol, and Agent-to-Agent communication models;
- Balance performance, latency, scalability, reasoning overhead, and data sensitivity considerations in architectural decisions;
- Establish authentication boundaries, trust layers, and governance guardrails for AI-enabled enterprise systems;
- Ensure compliance with enterprise security standards, data governance policies, and secure data exposure practices;
- Partner with security and platform teams to maintain reliable and trustworthy autonomous agent execution.
MUST HAVES
- 6+ years of experience designing enterprise integrations and distributed system architectures;
- Hands-on experience integrating systems with Salesforce;
- Deep expertise with Apex methods, advanced Salesforce Flows, custom prompt templates, and Salesforce APIs and connectors;
- Strong experience with REST APIs, gRPC, event-driven architectures, and enterprise synchronization patterns;
- Solid understanding of AI and LLM concepts including prompt engineering, context management, token optimization, multi-step AI workflows, agent orchestration, and semantic routing systems;
- Experience designing scalable and secure distributed systems;
- Strong understanding of authentication, security, trust boundaries, and data governance;
- Experience documenting architecture decisions, trade-offs, and technical strategy;
- Excellent collaboration and communication skills across engineering, platform, data, and security organizations;
- Upper-intermediate English level.
NICE TO HAVES
- Experience with Model Context Protocol (MCP);
- Experience with Agent-to-Agent (A2A) integrations;
- Experience with MuleSoft or enterprise middleware platforms;
- Familiarity with Salesforce Agentforce;
- Experience building or managing autonomous AI agents or micro-agent ecosystems;
- Experience with semantic tool discovery or AI-native integrations;
- Knowledge of Salesforce Bulk APIs and Salesforce Connect;
- Experience operating within large-scale enterprise AI environments.
PERKS AND BENEFITS
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
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