Principal Data and AI Architect

Salesforce Salesforce · Enterprise · Bogota, Colombia

This role is for a Principal Data and AI Architect at Salesforce, focusing on designing and operationalizing enterprise-grade data and AI architectures, specifically around the Agentforce platform and its integration with external AI agents. The role involves pre-sales technical design, shaping best practices for generative AI and agent interoperability, building prototypes, and acting as a technical advisor to customers. It requires expertise in AI/ML concepts, prompt engineering, agent lifecycle management, and integrating various data and AI components within a customer's ecosystem.

What you'd actually do

  1. 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.
  2. 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.
  3. Drive Prompt Engineering & Lifecycle Strategy - Lead prompt design, testing, monitoring, and iteration; define agent lifecycle best practices from development through refinement.
  4. Build Hands-On Demos & Prototypes - Co-create quick prototypes (<2 weeks) with AEs demonstrating integration between Agentforce and external agents or services.
  5. Lead Pre-Sales Workshops - Facilitate whiteboarding, deep-dive sessions, and quick enablement for customers and internal teams.

Skills

Required

  • Technical Pre-Sales/Consulting
  • Salesforce Agentforce
  • D360
  • External agent ecosystems
  • Prompt engineering
  • Agent lifecycle management
  • Hands-on prototype development
  • Machine learning concepts (predictive and generative AI)
  • Modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift)
  • Data ingestion patterns (batch, streaming, CDC)
  • Programming (e.g., JavaScript, Python, SQL, R)

Nice to have

  • Agent interoperability
  • Generative AI
  • Data Cloud
  • Cross-platform integrations
  • External agent frameworks
  • Voice integration via hyperscaler APIs
  • Data modeling
  • Identity resolution
  • Real-time vs. batch patterns
  • Data graph design
  • Activation strategies

What the JD emphasized

  • hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments
  • hands-on experience with Salesforce Agentforce and deep fluency with D360 and core Salesforce platform services
  • Strong understanding of external agent ecosystems and interoperability
  • Experience in prompt engineering, agent lifecycle management, and hands-on prototype development
  • Experience with machine learning concepts (predictive and generative AI)

Other signals

  • designing, validating, and operationalizing enterprise-grade data and AI architectures
  • guide customer Chief Data Officers and Enterprise Architects through emerging AI solutions
  • 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
  • Build hands-on prototypes and demos using Agentforce and integrated external agents
  • 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.