Support the sales cycle, covering the technical architecture, data strategy, and AI capabilities of Data Cloud and Agentforce.
Design, build, and present hands-on Proof of Concepts (POCs) and demonstrations for Data Cloud and Agentforce, showcasing their power and viability to technical stakeholders.
Explain the technical and business benefits of the Salesforce Customer 360 platform, with a strong focus on Data Cloud and Agentforce, to IT and technical stakeholders.
Understand, assess, and define technical customer requirements, focusing on AI, data management, and operational data utilization.
Advise CIO/CTO/CXO-level contacts and their IT teams on adopting cloud architectures, particularly how to leverage unified customer data and generative AI effectively.
Answer deep technical questions related to the capabilities and integration of Salesforce Data Cloud, AI, and Agentforce solutions.
Establish close relationships with customer technical stakeholders and act as a trusted advisor on data and AI strategy.
Respond to RFPs, focusing on the technical components of data, AI, and integration.
Coach and mentor fellow pre-sales colleagues on the technical aspects of Data Cloud and Agentforce.
Be a thought leader on specific technology topics like Generative AI, Data Strategy, and Hyper-Automation.
Drive innovation projects with impact (POCs, MVPs).
Maintain awareness of technical best practices related to data governance, security, and compliance.

Minimum Qualifications:

Proven track record of running hands-on, successful technical Proof of Concepts (POCs) for complex AI and/or Data solutions.
Relevant background and deep technical expertise in AI, Machine Learning, and/or Advanced Data Solutions (e.g., CDP, Data Warehousing, Data Lake, etc.).
Fluent in English (spoken and written).
Experience in pre-sales, e.g., solution engineering or technical architecture.
Deep knowledge of data architecture principles, including data modeling, ETL/ELT, data governance, and data quality.
Multi-year experience in software, system, or enterprise architecture disciplines.
Strong understanding of data integration patterns, data synchronization, and data volume considerations in a cloud environment.
Good understanding of the architectural principles of cloud-based platforms, including SaaS, PaaS, multitenancy, and multi-tiered infrastructure.
General interest in staying at the forefront of current technology developments and keeping knowledge up to date.

Preferred Qualifications:

Direct experience with Salesforce Data Cloud, Agentforce, Marketing Cloud, or Service Cloud (Agentforce) solutions.
Experience with Large Language Models (LLMs) and Generative AI architectures.
Salesforce Certified Architect or relevant Data/AI certifications (e.g., AWS, Azure, GCP Data/ML certifications).
Knowledge of relevant data privacy and compliance requirements is a plus.