Salesforce AI Integration Architect ID68517
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. Meet Our Recruitment Process Application → Coding Challenge → Video Interview → Technical Interview or Hiring Manager Interview Each step helps us understand your skills and overall fit. If it’s a match, you’ll receive an offer.