Platform Engineering Lead

REQUIREMENTS

Essential

• 9+ years of experience in Salesforce platform engineering, enterprise architecture or technical leadership roles.
  
• Master’s degree in Computer Science, Engineering or a related field
  
• Deep, hands-on Salesforce development and administration experience.
  
• Proven full-stack development experience and operation at Lead Architect, Technical Architect or Principal Engineer level.
  
• Strong experience integrating Salesforce with enterprise systems such as ERP, HR and cloud platforms.
  
• Solid understanding of Salesforce data models, security architecture and performance constraints.
  
• Experience designing integration and cloud architectures across AWS or similar environments.
  
• Hands-on experience in API design, CI/CD pipelines and cloud infrastructure management, with version control and collaboration using Git and Jira.
  
• Proficiency in setting up and managing secure, scalable development environments and automation pipelines.
  
• Strong grasp of software architecture, including monolith-to-microservice transitions.
  
• Experience working with and holding external vendors to account.
  

Salesforce-Led Platform Architecture

• Lead the architecture, development and administration of ALU’s Salesforce platform across domains.
  
• Design and govern integrations between Salesforce and AWS, Oracle NetSuite, BambooHR and other platforms.
  
• Define and document data models, integration patterns and API standards involving Salesforce.
  
• Ensure architectural decisions are practical, scalable and aligned with institutional needs.
  
• Balance scalability, flexibility and cost-efficiency in architectural and implementation decisions.
  

Hands-on Development & Salesforce Administration

• Remain an active technical contributor through Salesforce development (Apex, LWC, integrations) and configuration.
  
• Oversee and, where required, perform Salesforce administration including security models, roles, permissions and environment management.
  
• Review code and configurations to ensure quality, performance and alignment with architectural standards.
  

Enterprise Integration & Cloud Architecture

• Design scalable, modular integration architectures using APIs, event-driven patterns or microservices where appropriate.
  
• Optimise and secure cloud and integration infrastructure, particularly within AWS.
  
• Ensure integrations are resilient, observable and well documented in production.
  
• Ensure appropriate monitoring, logging and observability are in place across integrations and platforms to support operational stability and incident response.
  

Engineering Standards, Governance & Documentation

Establish and enforce technical standards across Salesforce and integrated platforms, including:

• async processing and integration patterns
  
• error handling and resilience approaches
  
• naming conventions and data ownership
  
• documentation and architectural decision records
  
• Define where technical knowledge is captured and how it is maintained over time.
  
• Influence and continuously improve delivery models across teams and vendors, ensuring work moves predictably from design through to production.
  

DevOps, Version Control & Release Discipline

• Define and own the version control and Git strategy across Salesforce and integrated platforms.
  
• Establish CI/CD pipelines and release management practices, ensuring environment parity across development, QA and production.
  
• Ensure traceability, controlled releases and rollback strategies across vendors and teams.
  

Vendor & Technical Leadership

• Act as the technical authority across internal teams and external delivery partners.
  
• Review vendor designs and deliveries, challenge assumptions and enforce architectural standards.
  
• Mentor engineers and product teams, raising the overall technical and architectural bar.
  

Responsible Use of AI in Engineering

• Use AI tools to accelerate development, improve code reviews, enforce standards and support documentation.
  
• Contribute to a structured, responsible approach to AI use within engineering workflows.