Job Description

Salesforce Principal Technical Architect1

AI & MODERN TOOLING EXPERTISE

Candidates must demonstrate hands-on proficiency with next-generation AI tools, LLM platforms, and Salesforce AI capabilities:

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 where a declarative Flow serves better than complex Apex. This functional grounding is the difference between architectures that look good in PowerPoint and platforms that scale reliably in the real world.

Revenue Operations Depth

An Architect who understands CPQ approval hierarchies, revenue recognition rules, and deal desk commercial dynamics can design AI-assisted revenue platforms that Finance, Legal, and Audit teams will trust — not just approve under delivery pressure.

Clinical & Care Workflow Knowledge

Architects designing Agentforce agents for healthcare must understand what care coordinators actually do: which systems they navigate, what data they need instantly, and where clinical judgment must remain with humans. Without this, agents get designed for demo scenarios, not real clinical workflows that affect patient outcomes.

Sales & Customer Success Strategy

Understanding how Sales Leaders interpret forecasting dashboards, how CS teams define health scores, and how RevOps measures attribution allows architects to design Salesforce AI platforms that genuinely enhance commercial decision-making — not add complexity that the business quietly routes around.

Regulatory & Compliance Framework

Functional awareness of HIPAA, GDPR, SOC 2, HITRUST, and industry-specific regulatory requirements allows architects to proactively design compliant AI data flows, consent management architectures, and audit-ready Agentforce agent governance frameworks — avoiding costly security review rework.

KEY RESPONSIBILITIES

• Lead technical architecture across multi-cloud Salesforce implementations: from initial solution design through delivery governance, go-live, and post-production optimisation

• Define enterprise Agentforce Agent frameworks: govern agent taxonomy, topic hierarchy, skill libraries, action security models, and human escalation protocols across the organisation

• Design enterprise MCP (Model Context Protocol) server architecture: define which Salesforce objects, Apex actions, and APIs are exposed as structured context to enterprise LLMs — Claude, GPT-4o, Gemini — with appropriate access control and audit governance

• Establish and enforce AI development standards: Prompt Template versioning, LLM gateway configuration, Einstein Copilot skill library governance, and AI output validation frameworks

• Lead technical pre-sales: design winning solution architectures for Healthcare and Hi-Tech clients, present to CTO/CIO audiences, and own technical content in RFP responses and SOW definitions

• Define multi-org strategy, data residency architecture, platform scalability roadmaps, and technical governance for enterprise Salesforce estates

• Conduct Well-Architected Reviews, security architecture reviews, and technical debt remediation roadmap design across the Salesforce platform portfolio

• Mentor Technical Leads and Senior Developers on AI-native development patterns, CPQ architecture, Health Cloud compliance design, and Agentforce best practices

• Partner with MuleSoft architects to define API-led connectivity strategies integrating Salesforce with EHR, ERP, data platforms, and AI infrastructure ecosystems

AI & AGENTFORCE SPECIFIC RESPONSIBILITIES

• Define the enterprise Agentforce Architecture Blueprint: agent taxonomy, skill library governance, topic hierarchy, action security model, agent lifecycle management, and performance observability framework

• Design enterprise MCP server topology: govern which Salesforce tools and data objects are exposed to which LLMs, with what permission scope, data masking requirements, and comprehensive audit trails

• Establish Prompt Engineering governance: define Prompt Template standards, version control workflows, performance evaluation KPIs, and A/B testing frameworks for Einstein Copilot and external LLM integrations

• Architect LLM Gateway configurations within Salesforce: intelligent routing policies between Einstein LLMs, Anthropic Claude, OpenAI, and Azure OpenAI based on use case sensitivity, cost optimisation, and regulatory compliance

• Define responsible AI and AI safety standards for enterprise deployments: hallucination guardrail design, PII redaction in prompt pipelines, bias monitoring, and mandatory human-in-the-loop requirements for regulated Healthcare and Financial Services deployments

• Design AI observability architecture: instrument Agentforce agent telemetry, prompt success rates, fallback trigger patterns, and resolution metrics into CRM Analytics and Data Cloud executive dashboards

• Champion AI-augmented engineering practices: standardise Cursor, Claude, and GitHub Copilot adoption across the engineering organisation with IP protection guardrails, code review governance, and productivity measurement frameworks

TECHNICAL SKILLS & QUALIFICATIONS

NICE TO HAVE

• Salesforce Certified Technical Architect (CTA) credential or Board-ready within 12 months

• Salesforce Industries (Vlocity) for Health Cloud or Communications vertical implementations

• HITRUST, GDPR, FedRAMP compliance design experience within Salesforce context

• Salesforce + Snowflake / Databricks data lakehouse integration architecture

• Agentic AI framework experience: LangChain, CrewAI, AutoGen alongside Salesforce Agentforce

• Published thought leadership, conference keynotes, or Salesforce MVP / community recognition

SOFT SKILLS & MINDSET