Salesforce Technical Architect
About this role
ROLE OVERVIEW
We are seeking a visionary Salesforce Technical Architect with 12- 15 years of exp, who defines the AI-native future of enterprise Salesforce platforms. You will lead architecture decisions across multi-cloud Salesforce ecosystems, design Agentforce Agent frameworks at enterprise scale, define Model Context Protocol (MCP) integration strategies, and govern how AI tools like Claude, Codex, and Cursor are embedded into the engineering lifecycle. Your deep functional understanding of Healthcare, Hi-Tech, and revenue operations — combined with architectural mastery — enables you to translate complex business strategies into resilient, scalable, AI-powered Salesforce platforms that deliver measurable, auditable business outcomes. You are the person in the room who can speak the language of the CFO, the CIO, the Chief Medical Officer, and the Lead Developer — with equal authority.
Department
Architecture
Reports To
VP Engineering
Industry Focus
Healthcare, Hi-Tech, Financial Services, Retail & Manufacturing
Engagement
Full-Time | Strategic Programs & Pre-Sales
Certifications
Salesforce CTA (or in progress), Application / System Architect, AI Specialist
AI & MODERN TOOLING EXPERTISE
Candidates must demonstrate hands-on proficiency with next-generation AI tools, LLM platforms, and Salesforce AI capabilities:
CORE AI PLATFORMS & LLMS
Claude (Anthropic) — Architecture & Dev
OpenAI GPT-4o / Codex
GitHub Copilot Enterprise
Cursor IDE (team governance)
Amazon Bedrock / Azure OpenAI
Google Vertex AI
SALESFORCE AI & AGENTFORCE LAYER
Agentforce Platform Architecture
Einstein Copilot Studio
Prompt Builder & LLM Gateway
Model Context Protocol (MCP)
Einstein Prediction Builder
Data Cloud AI Segmentation
Revenue Intelligence AI
DEVELOPER PRODUCTIVITY & DEVOPS
Salesforce Well-Architected Framework
SFDX / Salesforce CLI
Copado / Gearset DevOps
MuleSoft Architecture
Heroku / Salesforce Functions
LeanIX / Ardoq (EA tooling)
SALESFORCE CLOUD EXPERTISE (ANY OF 2 CLOUDS AS MENTIONED BELOW)
Sales Cloud
Architect enterprise Sales Cloud platforms spanning global territory hierarchies, multi-org topologies, AI-assisted pipeline management, Revenue Intelligence, and Agentforce Sales Agent frameworks. Define scalable data models and AI scoring architectures supporting global sales operations.
Service Cloud
Design resilient omni-channel service architectures: Omni-Channel capacity modelling, Agentforce Service Agent frameworks with human-in-the-loop escalation design, Einstein Article Recommendations, Knowledge Graph integration, and AI-driven CSAT prediction. Define service AI governance and quality standards.
Experience Cloud
Architect multi-site, multi-audience Experience Cloud platforms with headless LWR architecture, identity federation (SSO / MFA / PKCE), AI personalisation layers, and API-first integration patterns for patient portals, partner hubs, and enterprise customer communities.
Revenue Cloud (CPQ, Billing, ARM)
Define enterprise CPQ architecture: multi-org quoting strategy, cross-cloud pricing governance, ERP integration blueprints (SAP, NetSuite), ASC 606-compliant ARM configuration standards, and Agentforce Deal Desk agent framework design. Govern CPQ customisation boundaries and technical debt.
Health Cloud
Architect HIPAA-compliant Health Cloud platforms: Care Program object frameworks, Interoperability Hub (FHIR R4) architecture, consent management design, prior auth automation, and AI-assisted care coordination agent frameworks. Define PHI data residency, encryption, and access control architectures.
Data Cloud & MuleSoft
Design enterprise data unification strategies: Data Cloud identity resolution, calculated insights governance, and real-time activation pipelines into Sales, Service, and Marketing Clouds. Define MuleSoft API-led connectivity governance, integration platform standards, and event-driven architecture patterns using Platform Events and CDC.
INDUSTRY DOMAIN KNOWLEDGE (ANY ONE OF FOLLOWING)
Healthcare & Life Sciences
Deep knowledge of Provider, Payer, MedTech, Pharma, and Biotech business models and their distinct multi-cloud Salesforce platform architectures
Experience architecting HIPAA-compliant multi-org Salesforce environments: PHI isolation, field-level encryption, Shield Platform Encryption, and comprehensive audit logging
FHIR R4 interoperability architecture: Salesforce Health Cloud Interoperability Hub, SMART on FHIR OAuth flows, and bidirectional EHR system sync (Epic, Cerner, Oracle Health)
Strategic understanding of value-based care, ACO structures, and population health management — and how Salesforce AI platforms operationalise clinical quality metrics
C-suite Healthcare presentation experience: presenting AI-powered Salesforce platform roadmaps to CIOs, CMIOs, and Chief Digital Officers in health systems
Hi-Tech & Software
Mastery of SaaS company Salesforce platform patterns: SDR-AE-CSM-Renewal lifecycle architecture, PLG motion integration design, and partner ecosystem platform strategy
AI-native ARR growth platform design: churn prediction models, expansion signal detection from product telemetry, and automated renewal orchestration via Agentforce
Multi-product, multi-region Salesforce platform architecture for scaling SaaS companies — from Series C growth through public enterprise scale
Product telemetry integration: how SaaS usage data flows from data warehouses (Snowflake, Databricks) into Salesforce via MCP/API to trigger intelligent Sales and CS actions
M&A integration architecture: multi-org consolidation strategy, data migration blueprints, and technical debt rationalisation for acquired company Salesforce estates
FUNCTIONAL KNOWLEDGE (FOUNDATION FOR AI SOLUTIONS)
Deep functional knowledge enables professionals to design AI-powered Salesforce solutions that reflect real business intent — not just technical requirements. This is what separates good implementations from transformative ones.
Business Process Architecture Mastery
Technical Architects with genuine business process understanding can anticipate where AI agents will fail in production edge cases, where data models will break under operational load, and