Salesforce · Posted 2d ago
Principal AI Architect
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇬🇧 London, United Kingdom
- Contract
- Full-time
- Role
- ML engineering
- Source
- Stapply Data
Stack
- Snowflake
- Databricks
- SageMaker
- Vertex AI
- LangChain
- LLM
- Vector DB
- AWS
- GCP
- Azure
The posting
Join our team as a Principal AI Architect, where you will be a senior technical leader and trusted advisor to our customers. You will design, validate, and operationalize enterprise-grade data and AI architectures centered on Salesforce D360 and the Agentforce platform. This role requires expertise in data engineering, platform architecture, and applied AI. You will work closely with Account Executives and Product teams to ensure customers realize the full value of the platform. Additionally, you will shape best practices around generative AI, agent interoperability, and cross-platform integrations.
- Act as a senior technical leader and trusted advisor to customers, responsible for designing and operationalizing enterprise-grade data and AI architectures. - Lead pre-sales technical design by analyzing customer needs and recommending solutions aligned with Agentforce capabilities. - Shape best practices around generative AI, agent interoperability, prompt engineering, Data Cloud, and cross-platform integrations.
- Rapid Prototyping & Whiteboarding: Demonstrated ability to lead technical discovery workshops and co-create rapid proof-of-value prototypes (<2 weeks) for C-suite stakeholders (CDO, CTO, Enterprise Architects) - Technical Pre-Sales & Solution Engineering: 7+ years in customer-facing technical pre-sales, solution architecture, or technical advisory, partnering side-by-side with Account Executives (AEs) to drive enterprise deal cycles and business outcomes - Enterprise AI & Hyperscaler Ecosystem Depth: Proven experience designing and delivering AI, GenAI, and Data architectures within platforms such as AWS (Bedrock/SageMaker), Microsoft (Azure AI Foundry/Copilot), Databricks, Google Cloud (Vertex AI), Snowflake, or Palantir - Agent Interoperability & Open Standards: Experience with Retrieval-Augmented Generation (RAG), prompt engineering, background/conversational agents, voice AI integrations, or open protocols (e.g., Model Context Protocol - MCP, A2A) - Hands-On Modern AI & Agentic Builder Experience: Direct hands-on experience building, prototyping, or solutioning with frontier LLMs and modern AI tools—including OpenAI, Claude, LangChain / LangGraph, Cursor, or multi-agent orchestration frameworks - Education: BS/MS in Computer Science, Artificial Intelligence, Engineering, or equivalent technical field - Multi-Modal & Advanced AI Frameworks: Experience with voice pipelines, MLOps, vector search, or custom model fine-tuning - CRM / Salesforce Context: Prior familiarity or hands-on experience with Salesforce CRM, Agentforce Studio, or Data Cloud (D360)