Technical Architect, SMB Pre-Sales

Salesforce•New York, NY

7d•$148,190 - $217,980•Hybrid

About The Position

As an SMB Technical Architect, you are a pre-sales, customer-facing expert for our fastest-growing customers. You apply broad technical skills and business acumen to help sales teams align Salesforce AI, Data, and Security solutions with our customers’ data and AI transformation strategies. You will act as a subject matter expert in business strategy, application architecture, data, integration, security, governance, and AI. You will use a consultative approach to understand customer business and technical requirements and determine optimal data/application/security/AI architectures for customers based on product knowledge, industry standards, and customer needs. You will also develop repeatable propositions and go-to-market strategies for sales teams.

Requirements

Hands-on experience with cloud data warehouse and lakehouse platforms (Snowflake, Databricks, BigQuery, Redshift, Azure Synapse, or equivalent)
Strong SQL skills and comfort with data modeling across structured, semi-structured, and unstructured data
Practical experience with agentic AI or generative AI
Deep knowledge of enterprise data platforms and cloud architectures (AWS, GCP, or Azure — including data services, networking, identity, security, and governance)
Data management fundamentals: data modeling, MDM, identity resolution, data quality, governance, and lineage
Integration principles: APIs, event streaming (Kafka/Pub-Sub), ETL/ELT patterns
Principles of network, application, and information security
Ability to translate complex business and technical requirements into a compelling solution narrative for executive, technical, and business audiences
Strategic problem solver and thought leader; comfortable at the C-suite level
Lifelong learner - inquisitive, practical, passionate about technology and sharing knowledge
Willing and able to travel domestically (1-2 times per quarter)
Bachelor's degree in Computer Science, MIS, Data Science, Software Engineering, or other STEM field (or equivalent experience)

Nice To Haves

Deep understanding of modern lakehouse and cloud data platform patterns for unifying, harmonizing, and activating enterprise data. This includes designing data pipelines, semantic layers, and feature stores that prepare and enrich data for AI and agent-based applications
Experience designing persistent context layers for AI agents, including how structured and unstructured data feeds agent memory, how data schemas serve as server-side context, and how a unified data platform acts as the persistent knowledge base and scratchpad across agentic loops
Experience architecting and integrating generative AI solutions into enterprise systems, including API gateways, model management platforms, embedding pipelines, vector databases, and data flows necessary for serving LLMs at scale in production

Responsibilities

Act as a subject matter expert in business strategy, application architecture, data, integration, security, governance, and AI.
Use a consultative approach to understand customer business and technical requirements
Determine optimal data/application/security/AI architectures for customers based on product knowledge, industry standards, and customer needs
Develop repeatable propositions and go-to-market strategies for sales teams
Talk about the security, cost, and governance tradeoffs of LLMs v. Salesforce AI tools.
Speak to the advantages of deterministic v. probabilistic AI and when to build v. go OOB.
Advocate for the strengths of Salesforce as a platform and explain why vibe-coding a CRM will fail.
Define integrations with other systems and create a data architecture that makes sense based on customer priorities.