Enterprise AI & Data Cloud Architect (Pre-Sales)

salesforce.com, inc.; Austin (TX); On-site; USD 173,000 - 232,000; Full time

Job summary

Salesforce is seeking a Data & AI Cloud Technical Architect to serve as a pre-sales, enterprise domain expert blending data architecture with AI strategy. You will guide customers through data lakehouse architectures, ensure scalable AI deployments, and collaborate with sales to craft compelling propositions.

The role requires hands-on experience with cloud data platforms, ML workflows, and governance frameworks, across customer-facing engagements in a fast-paced environment.

Qualifications

• Hands-on experience with cloud data warehouses and lakehouse platforms.
• Strong SQL skills and data modeling across structured, semi-structured, and unstructured data.
• Familiarity with ML fundamentals and agentic/ generative AI concepts.
• Experience with production-grade data and AI solutions across enterprise environments.
• Python proficiency and ability to build prototypes quickly.

Responsibilities

• Lead technical and business discussions around enterprise data and AI programs from strategy to deployment.
• Develop repeatable data/AI propositions and go-to-market strategies with sales teams.
• Advise customers on data governance, privacy, and security in data-intensive environments.
• Create reference architectures and enablement sessions for customers and partners.

Skills

Cloud data platforms

SQL

Data modeling

dbt / Spark

ML fundamentals

Agentic AI experience

Python

Leadership

Education

B.S Computer Science or related

Tools

Snowflake

Databricks

BigQuery

Redshift

Azure Synapse

Job description

Salesforce is seeking a Data & AI Cloud Technical Architect to serve as a pre-sales, enterprise domain expert blending data architecture with AI strategy. You will guide customers through data lakehouse architectures, ensure scalable AI deployments, and collaborate with sales to craft compelling propositions.

The role requires hands-on experience with cloud data platforms, ML workflows, and governance frameworks, across customer-facing engagements in a fast-paced environment.