Technical Architect 8

Overview

As an AI and Data Technical Architect, you will lead the design and validation of enterprise-grade data and AI architectures centered on Salesforce D360 and the Agentforce platform. You’ll guide executives and architects through complex integrations with hyperscalers, data lakes, and governance frameworks, ensuring scalable and secure solutions. You’ll collaborate with sales and product teams to demonstrate value through hands-on prototypes and strong technical enablement. This role offers a chance to shape AI-driven enterprise architectures at scale within a market-leading AI CRM.

Responsibilities

• Lead pre-sales technical design aligning customer needs with Agentforce capabilities
• Shape best practices for generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations
• Collaborate with AEs and SEs to build demos and prototypes using Agentforce and external agents
• Develop thought leadership content (templates, whitepapers, enablement sessions) on agent lifecycle and integration strategy
• Serve as a central technical knowledge resource, enabling specialist teams and documenting best practices
• Map and integrate external agents from hyperscalers into Agentforce via open standards; design collaborative workflows
• Configure chat and background agents using Agentforce Studio/Agent Builder; integrate with hyperscaler channels
• Lead prompt design, lifecycle strategy, and governance for agent development and operation
• Create hands-on demos/prototypes (<2 weeks) demonstrating integration between Agentforce and external agents
• Facilitate pre-sales workshops and deep-dive sessions for customers and internal teams
• Advise on Data & Integration, ensuring cohesive architectures with Data Cloud (D360), CRM, and MuleSoft APIs
• Support early adoption and proof-of-value engagements by tuning agents and guiding self-sufficient enablement
• Oversee data modeling, identity resolution, real-time vs. batch patterns, and data graph design inside D360
• Develop accessible technical documentation and knowledge bases to empower teams

Key requirements

• 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments
• Strong understanding of external agent ecosystems and interoperability
• Proven track record in prompt engineering, agent lifecycle management, and prototype development
• AI & ML expertise with experience in predictive and generative AI; ability to communicate value to diverse audiences
• Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns
• Programming proficiency (JavaScript, Python, SQL, R) and data frameworks like pandas or Jupyter
• Excellent communication and presentation skills; ability to guide stakeholders toward impactful solutions
• Curiosity and continuous learning mindset, keen to explore new AI frameworks and technologies
• Excellent communication
• Curiosity
• Collaborative mindset
• Snowflake
• Databricks
• BigQuery

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