Principal AI Architect
MuleSoft - New York, New York, us, 10261
Work at MuleSoft
Overview
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Overview
You will: 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 to empower specialist teams across the organization. If you are naturally curious about AI, love diving into new technologies, and enjoy educating others while crafting solutions that deliver real business impact, we want to talk to you! Responsibilities
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. Build Hands-On Demos & Prototypes - Co-create quick prototypes (
Requirements
Technical Pre-Sales/Consulting: Several years in solutions engineering, architecture, or technical consulting, ideally in B2B SaaS. Hands-on experience with Salesforce Agentforce Strong understanding of external agent ecosystems and interoperability Proven track record 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. CRM & Data Knowledge: Familiarity with Salesforce CRM and modern data stacks; comfortable discussing governance, security, and integration. Hands-On Development: Proficiency in programming (e.g., JavaScript, Python, SQL) or Salesforce development (Apex, Lightning Web Components, etc.). Excellent Communication: Strong presentation skills; adept at explaining complex ideas and guiding stakeholders toward impactful solutions. Curiosity & Continuous Learning: Passion for exploring new AI frameworks, sharing insights, and experimenting with cutting-edge technologies. Preferred Requirements
Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A). Familiarity with prompt governance, observability, and monitoring frameworks. Background in cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce Flows). Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML: Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms (e.g., Google Vertex AI, AWS Sagemaker). Hands-on work with Generative AI, Large Language Models (LLMs), agent-based frameworks, and prompt engineering.
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