Principal Data and AI Architect

Overview of the Role

As an AI and Data Technical Architect, you will act as a senior, hands‑on technical leader and trusted advisor to our customers. You will be responsible for designing, validating, and operationalizing enterprise‑grade data and AI architectures centered on Salesforce D360 and the Agentforce platform. This role sits at the intersection of data engineering, platform architecture, and applied AI, requiring you to guide customer Chief Data Officers and Enterprise Architects through emerging AI solutions.

You will work side‑by‑side with Account Executives and Product teams to ensure customers realize the full value of the platform by designing scalable, secure solutions that integrate D360 into complex enterprise ecosystems—including hyperscalers, data lakes, and governance frameworks.

• Lead pre‑sales technical design by analyzing customer needs and recommending solutions aligned with Agentforce capabilities and integration with external agent frameworks.
• Shape best practices around generative AI, agent interoperability, prompt engineering, Data Cloud, and cross‑platform integrations.
• Collaborate with AEs and SEs to build hands‑on prototypes and demos using Agentforce and integrated external agents.
• Develop thought leadership content—demo templates, whitepapers, enablement sessions—focused on agent lifecycle, integration strategy, and technical effectiveness.
• Act as a central technical knowledge resource, proactively addressing internal technical inquiries and facilitating deep technical enablement.
• Understand Agent Interoperability—map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.
• Enable Conversational & Background Agents—use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels including voice via hyperscaler APIs.
• Drive Prompt Engineering & Lifecycle Strategy—lead prompt design, testing, monitoring, and iteration; define agent lifecycle best practices from development through refinement.
• Build Hands‑On Demos & Prototypes—co‑create quick prototypes (