What are the responsibilities and job description for the Senior Salesforce AI, Data Cloud & Analytics Architect position at Envision Technology Solutions?
Job Title: Senior Salesforce AI, Data Cloud & Analytics Architect
Location: Coral Springs, Florida OR Alpharetta, GA OR Berkeley Heights, New Jersey OR Frisco, Texas OR Brookfield, Wisconsin
Role Summary
We are seeking a Senior Salesforce AI, Data Cloud & Analytics Architect to serve as a hands-on enterprise Subject Matter Expert (SME) for Salesforce Agentforce, Data Cloud (Data 360), and Tableau Next. This role partners closely with Solution Architects, Sales, Service, Marketing, Data Platform, Security, and Business teams to design and deliver AI-powered, data-driven capabilities across the Salesforce ecosystem.
This individual is a hands-on technical and strategic contributor responsible for defining platform architecture, agent design patterns, data model strategy, semantic layer standards, integration approaches, governance practices, and analytics enablement for enterprise customer intelligence and AI-driven business processes.
Scope, Accountability & Impact (Senior Level)
Typically 10 years of experience in enterprise application architecture, CRM platforms, data platforms, analytics, AI-enabled solutions, or related technology domains.
5 years of Salesforce architecture experience supporting enterprise-scale Sales, Service, Marketing, Data Cloud, analytics, or platform implementation initiatives.
Serves as the primary SME for Agentforce, Data Cloud (Data 360), and Tableau Next architecture, implementation patterns, governance, and adoption strategy.
Defines reusable architecture standards, reference designs, platform guardrails, and technical roadmaps for Salesforce AI, data, and analytics capabilities.
Identifies and escalates platform, security, data quality, compliance, integration, scalability, and operational risks to Solution Architects, platform leadership, and enterprise architecture teams.
Influences enterprise strategy related to AI adoption, customer intelligence, data activation, analytics modernization, and Salesforce platform consolidation.
Required Qualifications
Direct hands-on experience with Salesforce Agentforce, Einstein AI, Salesforce AI capabilities, or enterprise AI-enabled platform solutions.
Direct hands-on experience with Salesforce Data Cloud / Data 360, including data modeling, ingestion, identity resolution, segmentation, activation, or governance.
Experience with Tableau Next, Tableau, or equivalent enterprise analytics and semantic modeling platforms.
Strong Salesforce platform architecture experience across Sales Cloud, Service Cloud, Platform, integrations, security model, metadata, automation, and data architecture.
Experience designing customer 360 solutions, semantic data models, governed data products, and enterprise reporting or analytics frameworks.
Strong understanding of APIs, event-driven architecture, data integration patterns, middleware, cloud platforms, and enterprise data platforms such as Snowflake.
Experience defining architecture standards, solution designs, technical roadmaps, governance models, and implementation patterns for enterprise platforms.
Strong knowledge of data governance, privacy, compliance, access controls, auditability, and security expectations in regulated enterprise environments.
Excellent executive communication, stakeholder management, technical translation, documentation, and cross-functional leadership skills.
Preferred / Strong Plus Qualifications
Salesforce Certified Technical Architect (CTA) or Salesforce Architect-level certifications.
Salesforce Data Cloud Consultant Certification.
Salesforce AI Specialist, AI Associate, or related Salesforce AI certifications.
Tableau certifications or hands-on experience delivering enterprise Tableau analytics solutions.
Experience with Snowflake, Snowflake Cortex, semantic layers, AI/ML platforms, or enterprise data lakehouse / medallion architecture patterns.
Experience integrating Salesforce with Snowflake, AWS, Azure, Google Cloud, middleware, API gateways, or enterprise data platforms.
Experience leading enterprise AI governance, Responsible AI adoption, platform modernization, or customer intelligence initiatives.
Experience within financial services, payments, fintech, or other highly regulated industries.
Experience working in Agile delivery models with product owners, architects, engineering teams, QA, security, and operations teams.