Technical Architect, SMB Pre-Sales

Salesforce•New York, NY

23h•$162,960 - $217,980

About The Position

As an SMB Technical Architect, you are a pre-sales, customer-facing expert for Salesforce’s fastest-growing customers. You apply broad technical skills and business acumen to help sales teams align Salesforce AI, Data, and Security solutions with customers’ data and AI transformation strategies. You 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, and AI architectures based on product knowledge, industry standards, and customer needs; and develop repeatable propositions and go-to-market strategies for sales teams. Technical Architects apply expertise across the Salesforce ecosystem, including AIforce, Agentforce, Customer 360, and Data 360. This includes explaining security, cost, and governance tradeoffs between LLMs and Salesforce AI tools; discussing deterministic versus probabilistic AI and when to build versus use out-of-the-box solutions; advocating for Salesforce as a platform; and defining integrations and data architectures based on customer priorities. The role involves domestic travel one to two times per quarter.

Requirements

Hands-on experience with cloud data warehouse and lakehouse platforms such as 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, including AWS, GCP, or Azure data services, networking, identity, security, and governance.
Knowledge of data management fundamentals, including data modeling, MDM, identity resolution, data quality, governance, and lineage.
Knowledge of integration principles, including APIs, event streaming such as Kafka or Pub/Sub, and ETL/ELT patterns.
Knowledge of network, application, and information security principles.
Ability to translate complex business and technical requirements into a compelling solution narrative for executive, technical, and business audiences.
Strategic problem-solving and thought leadership; comfort engaging at the C-suite level.
Inquisitiveness, practicality, passion for technology, and willingness to share knowledge.
Willingness and ability to travel domestically one to two times per quarter.
Bachelor’s degree in Computer Science, MIS, Data Science, Software Engineering, or another 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, including data pipelines, semantic layers, and feature stores for AI and agent-based applications.
Experience designing persistent context layers for AI agents, including structured and unstructured data feeding agent memory, schemas serving as server-side context, and unified data platforms acting as a 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 for serving LLMs at scale in production.

Responsibilities

Act as a pre-sales, customer-facing technical expert for SMB customers.
Align Salesforce AI, Data, and Security solutions with customers’ data and AI transformation strategies.
Serve as a subject matter expert in business strategy, application architecture, data, integration, security, governance, and AI.
Consult with customers to understand business and technical requirements.
Determine optimal data, application, security, and AI architectures based on product knowledge, industry standards, and customer needs.
Develop repeatable propositions and go-to-market strategies for sales teams.
Explain AI, platform, data, integration, security, cost, and governance considerations across Salesforce’s ecosystem.
Travel domestically one to two times per quarter.