Salesforce / Agentforce, AI Platform Integration Architect

System Orchestration & Blueprinting

• Architect end-to-end integration designs connecting Indeed s internal AI co-worker and related data platform services to Salesforce Agentforce environments

Pattern Optimization & Decisioning

• Apply rigorous architectural frameworks to choose the correct integration pattern (Traditional APIs, Model Context Protocol, or Agent-to-Agent) based on:

• Transaction volume
• Reasoning overhead
• Latency boundaries
• Data sensitivity

Agent Specialization Management

• Design modular agent structures to avoid monolithic, overloaded reasoning engines
• Enforce governance limits (e.g., maintaining under 10 topics per agent) by delegating complex tasks across specialized autonomous micro-agents

Cross-Functional Collaboration

• Work directly with Data Engineers, Salesforce Administrators, Core Platform Architects, and Security Operations
• Maintain unified API contracts and clean semantic understanding across all endpoints

Security and Trust Governance

• Establish explicit trust filters, secure authentication boundaries, and data exposure guardrails
• Protect sensitive corporate assets while maintaining fluid agent execution

• Solid understanding of Large Language Model (LLM) orchestration, prompt engineering, context windows, and token conservation
• Experience designing autonomous routing systems that leverage semantic understanding to execute multi-step tool calls

Enterprise Integration

• Proven expertise in high-scale data synchronization patterns
• Masterful command of REST, gRPC, and event-driven architectures (e.g., Salesforce Pub/Sub API) to coordinate distributed cloud systems

Salesforce Customization

• Deep familiarity with wrapping complex backend processes into agentic tools via:

• Invocable Apex methods
• Advanced Salesforce Flows
• Custom prompt templates

Architectural Governance

• Experience authoring comprehensive Architectural Decision Records (ADRs) that clearly map High-Level Requirements (HLRs) against technical constraints and explicit trade-offs

Must-Have Skills (Additional)

• Strong experience with enterprise integrations and system architecture
• Strong Apex methods, advanced Salesforce Flows, and custom prompt templates
• Experience with APIs (REST, gRPC, event-driven architectures)
• Experience integrating systems with Salesforce
• Knowledge of AI/LLM concepts such as:

• Prompt engineering
• Context management
• Multi-step AI workflows
• Agent orchestration

• Experience designing scalable and secure distributed systems
• Experience with Salesforce tools such as:

• Salesforce Flows
• APIs and connectors

• Understanding of security, authentication, and data governance
• Experience documenting architecture decisions and technical trade-offs
• Strong collaboration skills across engineering, data, and security teams

Nice-to-Have (Preferred)

• Experience with Model Context Protocol (MCP)
• Experience with Agent-to-Agent (A2A) integrations
• Experience with MuleSoft or 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 Bulk APIs and Salesforce Connect
• Experience working in large-scale enterprise AI environments