Job Description

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

- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;

- 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.