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Salesforce Data Cloud​/Agentforce SA

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: K2U
Full Time position
Listed on 2026-09-06
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Data Cloud/Agentforce Solution Architect- 6+ Months

Need a strong Data Cloud and Agentforce Architect on urgent basis.

End Date 12/31 with possibility of extension.

Agentforce — the agent layer ("the brain"). Runs the live call: detects intent (buy/modernize vs. warranty vs. issue), runs discovery, recommends a product, qualifies and scores the lead, and orchestrates the actions (Create Lead, dealer lookup, warranty verify, escalation). Everything else feeds it or executes for it.

Data Cloud — the unified data foundation. Resolves the caller into one profile across CRM, warranty/asset, and marketing data via identity resolution; gives the agent a real-time complete-customer view to ground recommendations and personalization; computes lead score / propensity / segments; and enriches the created lead. Without it, the agent reasons on partial, siloed data.

Service Cloud Voice + Amazon Connect — the channel. Telephony backbone: PSTN call handling, real-time transcription and sentiment, the medium the voice agent runs on, and the path for human escalation and dealer warm-transfer.

Sales Cloud / CRM core — the system of record. Holds the Lead, the Product2 catalog the agent maps to, dealer/account records, and routing/assignment plus conversion-to-opportunity downstream. The lead the agent creates lands and gets worked here.

Agentforce Actions (Apex / Flow / MCP) — the integration + guardrail layer. The deterministic capabilities the agent calls (Create Lead, Identify Nearest Dealership, Verify Customer & Warranty), the API/MCP connectivity to external systems (dealer locator, warranty/asset platform), and the grounding contracts that stop the agent inventing data.

Knowledge — grounding for recommendations. The product/spec articles the agent uses to recommend the right unit for the caller's area, budget, and preference instead of guessing.

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