Principal Data and AI Architect

Salesforce Salesforce · Enterprise · Buenos Aires, Argentina

Salesforce is seeking a Principal Data and AI Architect to design, validate, and operationalize enterprise-grade data and AI architectures centered on their D360 and Agentforce platforms. This role involves leading pre-sales technical design, shaping best practices for generative AI and agent interoperability, building prototypes, and acting as a central technical knowledge resource for customers and internal teams.

What you'd actually do

  1. Lead pre-sales technical design by analyzing customer needs and recommending solutions aligned with Agentforce capabilities and integration with external agent frameworks.
  2. Shape best practices around generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations.
  3. Collaborate with AEs and SEs to build hands-on prototypes and demos using Agentforce and integrated external agents.
  4. Develop thought leadership content—demo templates, whitepapers, enablement sessions—focused on agent lifecycle, integration strategy, and technical effectiveness.
  5. Act as a central technical knowledge resource, proactively addressing internal technical inquiries, facilitating deep technical enablement, and documenting best practices to empower specialist teams across the organization.

Skills

Required

  • Technical Pre-Sales/Consulting - 7+ years of hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments.
  • Salesforce Expertise - Hands-on experience with Salesforce Agentforce and deep fluency with D360 and core Salesforce platform services.
  • External Ecosystem Knowledge - Strong understanding of external agent ecosystems and interoperability.
  • Proven Track Record - Experience in prompt engineering, agent lifecycle management, and hands-on prototype development.
  • AI & ML Expertise - Experience with machine learning concepts (predictive and generative AI), plus the ability to communicate value to diverse audiences.
  • Data Stack Knowledge - Deep expertise in modern cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) and data ingestion patterns (batch, streaming, CDC).
  • Hands-On Development - Proficiency in programming (e.g., JavaScript, Python, SQL, R) and data frameworks like pa

Nice to have

  • Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.
  • 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 from development through refinement.
  • 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, empowering specialist teams to handle technical discussions confidently.

What the JD emphasized

  • hands-on technical leader
  • hands-on prototypes
  • hands-on experience
  • Hands-On Development

Other signals

  • Designing and implementing enterprise-grade data and AI architectures
  • Guiding customer Chief Data Officers and Enterprise Architects through emerging AI solutions
  • Leading pre-sales technical design by analyzing customer needs and recommending solutions aligned with Agentforce capabilities and integration with external agent frameworks
  • Shaping best practices around generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations
  • Collaborating with AEs and SEs to build hands-on prototypes and demos using Agentforce and integrated external agents