Pre-Sales Data and AI Architect (Solution Engineering, United States)

Join Salesforce as a Pre-Sales Data and AI Architect, where you will be the expert thought leader and senior field specialist for customers evaluating, implementing, and expanding their use of Salesforce Data 360 (Data Cloud), Agentforce, and the broader enterprise data and AI ecosystem. You will help customers translate their data and AI ambitions into practical, actionable architectures, and lead customer architectural discussions around various topics including data structures, AI readiness, identity management, governance, integration, automation, and business value.

• Assister les clients dans l'évaluation, la mise en œuvre et l'expansion de leur utilisation de Salesforce Data 360 (Data Cloud) et de l'écosystème de données et d'IA.
• Travailler à l'intersection de l'architecture technique, de l'ingénierie des solutions et de l'IA appliquée pour traduire les ambitions des clients en architectures pratiques.
• Diriger les discussions architecturales avec les clients sur Data 360, Agentforce, les structures de données, la préparation à l'IA, la gestion de l'identité, la gouvernance, l'intégration, l'automatisation et la valeur commerciale.

• The ability to distill and communicate complex technical ideas to executive and technical audiences
• Experience working across Sales, Product, Engineering, Support, and delivery or customer teams to move solutions from idea to execution
• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Data Science, other STEM degrees or equivalent work experience. Graduate study a plus
• Strong understanding of enterprise data, AI, integration, governance, security, privacy, and platform architecture concepts and patterns
• Demonstrated curiosity and learning velocity in emerging technologies — especially within the AI, data, automation, and agentic systems space
• 7+ years experience in technical architecture, enterprise architecture, solution engineering, consulting, implementation, software engineering, product development, or related work in complex enterprise environments
• A track record of shaping technical strategy with input from customers and /or stakeholders, validating solution approaches, and connecting business needs to technology decisions
• Salesforce Data 360 (Data Cloud), Agentforce, MuleSoft, Tableau, Informatica, or the broader Salesforce Platform
• Conversational AI, voice-enabled AI agents, real-time voice orchestration, telephony integrations, or multi-channel service experiences
• Modern data platforms such as Snowflake, Databricks, BigQuery, or RedShift, and the hyperscaler ecosystems around them
• AI agents, generative AI, AI governance and observability, external agent ecosystems, hyperscaler AI services, or enterprise automation
• Programming languages such as Python, common data structures and tooling, and AI-assisted development pipelines
• Building demos, prototypes, proofs of concept, workshops, reference architectures, or field enablement assets