Domain Architect – HR & Payroll

• Azure data layer – Azure SQL, Synapse / Microsoft Fabric and Data Lake / Storage, with supporting data-integration services. Awareness of AWS is nice to have.
• API-led integration (MuleSoft preferred) – system, process and experience APIs, with API design and lifecycle management.
• Enterprise solution architecture and design – across cloud-native, microservices and event-driven patterns.
• Security & compliance – security-by-design and awareness of the regulatory drivers relevant to TMF's operating model (DORA, GDPR), employee personal-data protection and data residency across jurisdictions.
• AI & GenAI awareness – working understanding of AI/ML and generative-AI capabilities (LLMs, AI agents, RAG, classification and extraction models) and how they apply to HR and payroll workflows – e.g. gross-to-net validation, payroll anomaly detection, document extraction and employee-query handling. Able to critically evaluate vendor AI offerings, distinguishing genuine capability from marketing and assessing model accuracy, hallucination and bias risk, explainability, human-in-the-loop controls, training-data provenance and data-handling. Assesses AI solutions against EU AI Act, DORA and GDPR obligations before embedding them into regulated payroll and HR processes.

KPIs / success metrics

• Demonstrable adherence to Enterprise Architecture standards
• Standardized workforce and payroll data model adopted across regions.
• Measurable reduction in payroll errors, regulatory and audit issues.
• Reusable integration patterns for payroll, HCM and statutory reporting.
• Improved time-to-onboard for new countries and payroll flows.

Ideal experience

• 12+ years in enterprise/solution architecture.
• Demonstrable exposure to payroll and/or HCM platforms.
• Experience designing and leading development teams building enterprise platforms end-to-end.
• Design a multi-country payroll processing and statutory compliance architecture.
• Design a global payroll platform supporting multiple in-country providers, aggregator models and gross-to-net variability.
• Approach to payroll accuracy, controls, auditability, scalability and regulatory variability across regions.
• Handling employee-data privacy and residency across jurisdictions.
• Evaluate a vendor’s AI-enabled payroll or HR offering – how would you validate its claims, test accuracy and explainability, design human oversight, and govern its use under the EU AI Act and DORA
• Awareness of TOGAF framework