Principal AI Architect

Salesforce Salesforce · Enterprise · London, United Kingdom

Principal AI Architect at Salesforce, focusing on designing and operationalizing enterprise-grade data and AI architectures centered on the Agentforce platform and D360. The role involves leading 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 deep expertise in modern cloud data platforms, programming, and machine learning concepts, with a focus on integrating Salesforce with external agent frameworks.

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 - 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 pandas or Jupyter.
  • Excellent Communication - Strong presentation skills; adept at explaining complex ideas and guiding stakeholders toward impactful solutions.

Nice to have

  • Advanced Integration - Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A).
  • Governance & Observability - Familiarity with prompt governance, observability, monitoring frameworks, responsible AI and compliance best practices
  • Cross-Platform Background - Background in cro

What the JD emphasized

  • hands-on technical leader
  • designing, validating, and operationalizing enterprise-grade data and AI architectures
  • guide customer Chief Data Officers, CxOs and Enterprise Architects
  • hands-on prototypes and demos
  • hands-on experience designing and delivering data, analytics, and AI architectures in enterprise environments
  • Hands-On Development

Other signals

  • AI CRM
  • Agentforce platform
  • generative AI
  • agent interoperability
  • prompt engineering
  • cross-platform integrations
  • external agent frameworks
  • enterprise-grade data and AI architectures