Salesforce AI Platform Integration Architect

Must-Have Skills

• Strong understanding of Agentic AI architecture, including Large Language Model (LLM) orchestration, prompt engineering, context management, token optimization, and multi-step AI workflows.
• Experience designing autonomous routing systems that leverage semantic understanding and agent orchestration to execute complex tool calls and workflows.
• Proven expertise in enterprise integrations and large-scale distributed system architecture.
• Strong experience with REST APIs, gRPC, and event-driven architectures, including platforms such as Salesforce Pub/Sub API.
• Deep experience integrating enterprise systems with Salesforce.
• Advanced knowledge of Salesforce customization, including:
• Invocable Apex methods
• Advanced Salesforce Flows
• Custom prompt templates
• APIs and connectors
• Experience designing scalable, secure, and highly available distributed systems.
• Strong understanding of security, authentication, data governance, and trust boundaries in enterprise environments.
• Experience documenting architecture decisions, technical constraints, and trade-offs through Architectural Decision Records (ADRs) or similar frameworks.
• Excellent collaboration skills across engineering, data, platform, and security teams.

Preferred Qualifications

• Experience with Model Context Protocol (MCP)
• Experience with Agent-to-Agent (A2A) integrations
• Experience with MuleSoft or other 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 within large-scale enterprise AI environments

Position Overview

The GTM Core team at Indeed is seeking a highly skilled and strategic AI Platform Integration Architect to help drive the next generation of enterprise automation. This role will bridge internal data architectures with Salesforce’s advanced agentic AI capabilities, with a primary focus on scaling and evolving an internally developed autonomous AI co-worker platform.

Key Responsibilities

System Orchestration & Architecture

• Design and architect end-to-end integrations between internal AI platforms, data services, and Salesforce Agentforce environments.
• Define scalable integration blueprints that support secure and intelligent autonomous workflows across enterprise systems.

Integration Strategy & Decision Frameworks

• Evaluate and select the appropriate integration pattern — including traditional APIs, Model Context Protocol (MCP), or Agent-to-Agent (A2A) frameworks — based on:
• Transaction volume
• Latency requirements
• Reasoning complexity
• Data sensitivity
• Operational scalability

Agent Architecture & Governance

• Design modular, specialized agent ecosystems that prevent monolithic reasoning models.
• Implement governance standards and delegation strategies across autonomous micro-agents to improve scalability and maintainability.
• Establish operational boundaries, including topic/domain limits per agent.

Cross-Functional Collaboration

• Partner closely with Data Engineering, Salesforce Administration, Platform Architecture, and Security Operations teams.
• Maintain clean API contracts, semantic consistency, and integration standards across all enterprise endpoints.

Security & Trust Governance

• Define authentication boundaries, trust filters, and data access guardrails to protect sensitive enterprise assets.
• Ensure autonomous systems operate securely while maintaining efficient agent execution and interoperability.