Technical Architect, SMB Pre-Sales
Mentions 'vibe-coding' as a negative example and focuses on robust AI and data architectures rather than quick vibe-coded CRM hacks.
About the Role
The SMB Technical Architect (Pre-Sales) is a customer-facing technical expert who partners with sales teams to design and align Salesforce AI, data, and security architectures for small-to-midsize business customers. The role focuses on solution architecture, data and integration strategies, and translating customer requirements into repeatable go-to-market propositions.
Job Description
Role
As an SMB Technical Architect (Pre-Sales) you act as a customer-facing subject-matter expert who helps sales teams align Salesforce AI, data, and security solutions with customers’ data and AI transformation strategies. You consult on application architecture, data, integration, security, governance, and agentic AI patterns and develop repeatable propositions and go-to-market strategies for sales teams.
Key Responsibilities
- Serve as a pre-sales technical lead and trusted advisor for SMB customers and sales teams.
- Use a consultative approach to gather business and technical requirements and translate them into solution narratives for technical and executive audiences.
- Design optimal data, application, security, and AI architectures based on product knowledge and industry standards.
- Define integrations, data architecture, and data flows to support AI and agent-based applications.
- Develop repeatable offerings and GTM strategies for sales enablement.
- Communicate tradeoffs around LLMs versus Salesforce AI tools and advise on deterministic vs probabilistic agent strategies.
Baseline Requirements
- Hands-on experience with cloud data warehouse and lakehouse platforms (Snowflake, Databricks, BigQuery, Redshift, Azure Synapse, or equivalent).
- Strong SQL skills and experience 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.
- Understanding of network, application, and information security principles.
- Ability to present technical solutions to executive (C-suite), technical, and business audiences; strategic problem solving and thought leadership.
- Bachelor’s degree in Computer Science, MIS, Data Science, Software Engineering, or equivalent experience.
- Willingness to travel domestically (~1–2 times per quarter).
Preferred / Advanced Experience
- Deep expertise in lakehouse and unified data architecture patterns, semantic layers, and feature stores.
- Experience designing persistent context layers and agentic memory architectures for AI agents.
- Experience architecting and integrating generative AI solutions at scale, including API gateways, model management, embedding pipelines, and vector databases.
Compensation & Benefits
- Typical base salary range listed: $148,190 - $198,170 annually (USD). Location-specific range (California, New York, and select metro areas): $162,960 - $217,980 per year.
- Role may be eligible for incentive compensation, equity, and benefits.
- Benefits include time-off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.
Logistics & Hiring Notes
- Salesforce uses AI tools to assist recruiters; humans make final hiring decisions.
- Reasonable accommodations are available during the application and recruiting process.