Field CAIO (AI & Agentic Ecosystem)

• The Field CAIO need to be credible enough to help a CDAIO shape their AI strategy and vision for enterprise AI at scale — and then translate that vision into the role Salesforce plays within it, connecting enterprise-wide AI ambition to what’s actually buildable and trustworthy on our platform
• The field’s go-to authority on LLMs and agentic implementations — not the hyperparameters or fine-tuning mechanics, but how to put the technology to real, measurable work based on the Salesforce Platform
• Sales-driven, C-level presence: CAIOs, CTOs, and business leaders treat you as the peer who can turn “we should use AI” into a funded, working plan
• Present at events, analyst briefings, and customer boards; publish points of view on what actually works in production AI versus what’s hype
• Own the hardest part of the AI story: getting tools out of the demo and into production, with the trust and transparency for a business to depend on them
• Translate AI capability into concrete business process improvement — help customers frame the problem, size the value, and pick the right first use case
• Bring hands-on architectural credibility on agentic patterns (orchestration, tool use, guardrails, observability) so customers trust what an agent will and won’t do
• Long-term trusted advisor to strategic accounts on their AI roadmap, beyond any single deal
• Build reference architectures and GTM narratives for new AI/agentic offerings ahead of launch
• Package proof points and playbooks — ideally drawn from your own track record of shipping AI products — that the wider architect community can reuse
• Co-own architecture patterns with AI ecosystem partners (hyperscalers, model providers, agent-framework vendors) to accelerate joint solutioning

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- Good tech depth on at least one Salesforce cloud and core/platform, and a good understanding of major features and capabilities of Salesforce offering
• Salesforce Platform: Solid working knowledge of Agentforce and at least one cloud (Data 360, Sales, Service, or Industry Clouds)
• Data Foundations: Enough data-platform fluency (cloud DWH/DL) to know when data quality is the real blocker to AI value
• Builder — has shipped an AI product, not just prototyped one
• Sales Instinct — genuinely enthusiastic, commercially driven
• Strong grasp of what makes production AI trustworthy: transparency, observability, guardrails, evaluation — able to speak to this with engineering and business audiences alike
• 10-15+ years in AI/ML, applied data science, or technical consulting, with recent deep focus on LLMs and agentic systems
• Production & Trust: Guardrails, governance, monitoring, and transparency patterns for deployed AI systems
• AI & Agentic: LLMs, RAG, vector stores, agent orchestration, MCP/A2A interoperability, evaluation/observability frameworks
• Applied AI-to-Value: Use-case framing, business process redesign, ROI measurement for AI initiatives
• Demonstrated C-level advisory experience, translating AI potential into business-process outcomes
• Storyteller — moves a room from “interesting demo” to “let’s fund this”
• Demonstrated track record of taking AI tools into production — ideally: built an AI product or company, and can show references for the business impact delivered to customers
• Degree or equivalent experience
• Pragmatist — cares about measurable business value over technical novelty
• Trust Broker — makes customers comfortable putting AI into production
• Fluent English required; additional EMEA languages a plus