1 day ago

Principal Data & AI Architect - Pre-Sales

Salesforce

Melbourne

1 day ago

Apply

Salesforce is hiring a Principal Data & AI Architect for a pre-sales role in Melbourne, Australia. This remote, full-time position involves designing and validating enterprise-grade data and AI architectures centered on Salesforce Data Cloud (D360) and Agentforce. The role requires 7+ years of experience in data, analytics, and AI architecture, with expertise in cloud data platforms and AI/ML concepts.

AI-enabledRemoteFull-timePrincipalPre-SalesConsulting

Principal Data & AI Architect - Pre-Sales

Apply

AI-enabledRemoteFull-timePrincipalPre-Sales

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

Remote

Experience Required

7 years

Employment Type

Full-time

Experience Level

Principal

Core Qualifications

Technical (Must-have)

Pre-SalesConsultingData ArchitectureAI ArchitectureMachine LearningGenerative AIPrompt EngineeringAgent Lifecycle ManagementSnowflakeDatabricksBigQueryAmazon RedshiftData IngestionJavaScriptPythonSQLRpandasJupyterCommunicationCuriosityContinuous Learning

Soft Skills

CommunicationCuriosityContinuous Learning

Preferred Qualifications

Technical (Nice-to-have)

Salesforce AgentforceSalesforce Data Cloud (D360)MCPA2ATensorFlowPyTorchMLOpsGoogle Vertex AIAWS SageMaker

Key Responsibilities

•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, facilitating deep technical enablement, and documenting best practices.
•Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A).
•Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels including voice via hyperscaler APIs.
•Lead prompt design, testing, monitoring, and iteration; define agent lifecycle best practices.
•Co-create quick prototypes (<2 weeks) with AEs demonstrating integration between Agentforce and external agents or services.
•Facilitate whiteboarding, deep-dive sessions, and quick enablement for customers and internal teams.
•Integrate Data Cloud (D360), CRM, MuleSoft APIs, and external agent endpoints ensuring cohesive architectures that align with compliance and governance policies.
•Occasionally assist in proof-of-value engagements post-sale by tuning agents and guiding customers toward self-sufficient enablement.
•Oversee data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.
•Create and manage accessible technical documentation, knowledge bases, and FAQ resources to rapidly resolve internal technical inquiries.

Pre-SalesData ArchitectureAIAgentforceData CloudRemoteFull-timePrincipalSalesforceAustralia

Core Qualifications

Technical (Must-have)

Soft Skills

CommunicationCuriosityContinuous Learning

Key Responsibilities

•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, facilitating deep technical enablement, and documenting best practices.

•Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A).

•Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels including voice via hyperscaler APIs.

•Lead prompt design, testing, monitoring, and iteration; define agent lifecycle best practices.

•Co-create quick prototypes (<2 weeks) with AEs demonstrating integration between Agentforce and external agents or services.

•Facilitate whiteboarding, deep-dive sessions, and quick enablement for customers and internal teams.

•Integrate Data Cloud (D360), CRM, MuleSoft APIs, and external agent endpoints ensuring cohesive architectures that align with compliance and governance policies.

•Occasionally assist in proof-of-value engagements post-sale by tuning agents and guiding customers toward self-sufficient enablement.

•Oversee data modeling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360.

•Create and manage accessible technical documentation, knowledge bases, and FAQ resources to rapidly resolve internal technical inquiries.