Salesforce AI Integration Architect

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

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 modular agentic AI systems using LLM orchestration, prompt engineering, and multi-step AI workflows, while developing integrations through Salesforce Flows, Apex methods, and custom prompt templates. The role requires deep expertise in enterprise security, data governance, and architectural decision-making across AI-native systems.

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;
Design and optimize modular agentic AI systems, avoiding monolithic reasoning architectures 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 comprehensive Architectural Decision Records (ADRs) documenting technical trade-offs, constraints, and High-Level Requirements (HLRs);
Evaluate and select optimal integration patterns including Traditional APIs, Model Context Protocol (MCP), and Agent-to-Agent (A2A) 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, Salesforce APIs and connectors;
Strong experience with REST APIs;
Solid understanding of AI/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.