Field CTO (Data & AI) in London

• This team sits at the centre of Salesforce’s GTM strategy in EMEA, connecting the dots between Data & AI Products, Product Marketing, Enablement, Customer Success, and the Partner Ecosystem — and operating across the full customer lifecycle to ensure customers don’t just buy Agentforce and Data360, but genuinely succeed with them
• As Distinguished Technical Architect, Data & AI, you are Salesforce’s most senior technical voice on Data and AI in EMEA — a Field Chief Data and AI Officer in practice, even when the room doesn’t know your title
• Be a compelling, credible voice for Data and AI at Salesforce events, industry conferences, analyst briefings, and customer roundtables across EMEA
• Present on stage and command a room — with the depth to hold a conversation with a Chief Scientist and the clarity to move a CEO to action
• Publish technical thought leadership (blogs, whitepapers, reference architectures) that shape how the market thinks about enterprise AI and data strategy
• Represent Salesforce’s architectural point of view in the external ecosystem — with partners, analysts, press, and the broader technical community
• Build and maintain a personal brand as a trusted authority on the intersection of Data, AI, and enterprise architecture
• Operate as a senior technical authority in Salesforce’s most strategic and complex EMEA deal cycles — not as an executive presence at meetings, but as a material influence on buying decisions, architectural direction, and adoption outcomes
• Engage at CDAO, CTO, and CIO level to shape enterprise data and AI strategy — connecting Salesforce’s platform to the customer’s most important business outcomes
• Lead architectural deep-dives, whiteboard sessions, and design sprints that give customers the confidence to make bold decisions on Agentforce and Data360
• Collaborate with AEs and SEs to build hands-on prototypes and proof-of-value demonstrations — targeting delivery in under two weeks — that make the architecture real and accelerate buying decisions
• Own technical architecture decisions at customer engagements: data modelling, identity resolution, real-time vs. batch patterns, data graph design, and activation strategies within D360
• Map and integrate external agents from hyperscalers (e.g., Copilot, Gemini) into Agentforce via open standards (MCP, A2A); advise customers on how these systems collaborate within their enterprise architecture
• Navigate ambiguous, high-stakes technical conversations with authority — knowing when to prescribe, when to co-design, and when to challenge
• Support early adoption engagements post-sale by tuning agents and guiding customers toward self-sufficient enablement
• Serve as a long-term trusted advisor to strategic customers — building relationships that outlast any single deal cycle
• Package and codify architectural patterns, reference designs, proof-of-concept frameworks, and technical playbooks that other Technical Architects across EMEA can deploy directly in their deal cycles
• Be an internal multiplier — elevating the architectural quality of the broader team through coaching, IP contribution, and program leadership
• Develop scalable enablement assets — including demo environments, architectural workshop templates, and POV accelerators — that compress time-to-value for the field
• Partner with Product and Engineering to translate field-driven architectural insights into roadmap input and product improvements
• Contribute to the global Architect community, sharing reusable IP and best practices that raise the bar across the function

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year

Fluency across the modern data and AI stack: cloud data platforms (Snowflake, Databricks, BigQuery), agentic frameworks, RAG, vector databases, LLM orchestration, data governance, and enterprise integration patternsHands-on proficiency in programming (e.g., Python, JavaScript, SQL) and data frameworksExperience with prompt engineering, agent lifecycle management, and hands-on prototype development15+ years of progressive experience in enterprise architecture, technical consulting, or technical pre-sales in Data and AI domainsDemonstrated experience engaging C-level executives (CDO, CTO, CIO, CDAO) as a trusted technical advisor — influencing architecture decisions, not just presenting in themTrack record of presenting at major industry events, publishing technical thought leadership, or building a recognized personal brand in the Data and AI ecosystemFluent English required; additional EMEA language skills are a strong plusDegree or equivalent relevant experience required. Experience will be evaluated based on the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.)Deep, hands-on technical expertise across enterprise data platforms, AI/ML, Generative AI, and agentic architectures — including Salesforce Agentforce, Data360, and the Salesforce platformExperience operating in complex, matrixed enterprise environments across multiple EMEA marketsUnderstanding of agent interoperability standards (MCP, A2A) and the broader external agent ecosystemProven ability to design and deliver reusable technical assets — reference architectures, POV frameworks, or architectural playbooks — at scaleExceptional communicator and storyteller — able to translate architectural complexity into board-level narratives and back againAgentforce & Salesforce Platform Deep architectural understanding of how Data and AI are activated within Salesforce — including Agentforce, Data360, Sales Cloud, Service Cloud, and Industry Clouds. Hands-on experience with Agentforce Studio and Agent Builder to configure conversational and background agents; integration with external channels including voice via hyperscaler APIs. Proficiency in prompt design, testing, monitoring, and iteration; familiarity with agent lifecycle best practices from development through refinement. Understanding of how external agents (Copilot, Gemini, etc.) integrate with Agentforce via open standards (MCP, A2A)Data Architecture & Platforms Cloud data platforms, SQL, ingestion pipelines (batch, streaming, CDC), ETL/ELT, data modelling, semantic layers, integration patterns, and the TCO trade-offs of building with hyperscalers vs. Salesforce. Deep familiarity with Informatica (IDMC) for enterprise data integration and MDM, alongside Snowflake, Databricks, BigQuery, and RedshiftAI & Agentic Architecture Foundational ML concepts, data preparation, Python, applied AI, Generative AI, prompt engineering, retrieval-augmented generation (RAG), vector stores, and agentic architectures. Hands-on familiarity with platforms like Databricks, Snowflake, SageMaker, or Vertex. Agent lifecycle management, observability, and governance frameworksAnalytics & BI Working knowledge of Tableau, PowerBI, or Looker and how they connect to enterprise data strategyIntegration Patterns MuleSoft APIs, hyperscaler SDKs, cross-platform integrations, and enterprise governance and compliance frameworks

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