- Lead, mentor, and develop a team of software engineers, fostering a high performance and growth-oriented culture.

- Promote responsible adoption of AI-assisted development tools (e.g., AI pair programming, code assistants, test generation tools) to enhance developer productivity while maintaining quality and security standards.

- Ensure engineers understand both the benefits and limitations of AI-generated outputs, reinforcing accountability and craftsmanship.

- Promote collaboration, psychological safety, engineering discipline, and accountability.

- Own the delivery of Azure-based payment systems that are resilient, fault tolerant, performant, and secure.

- Guide implementation of payment flows, including routing, orchestration, messaging, eventing, and integration patterns.

- Encourage the use of AI-supported design analysis and architecture validation tools where appropriate to improve solution robustness and consistency.

- Ensure solutions align with enterprise architecture standards, group engineering strategy, regulatory obligations, and secure AI usage policies.

- Embed modern engineering practices including CI/CD, trunk-based development, automated testing, DevSecOps, observability, infrastructure-as-code, and AI-assisted SDLC optimisation.

- Leverage AI to :

a. Improve test coverage through automated test case generation.

b. Enhance static code analysis and vulnerability detection.

c. Support documentation generation and knowledge discovery.

- Establish guardrails for safe and compliant use of AI tools in a regulated payments environment.

- Champion secure-by-design and resilient-by-default approaches across all delivery squads.

- Provide strong technical guidance on Azure-native services and patterns, including :

- Azure Kubernetes Service (AKS)

a. Azure Container Apps

b. Azure Functions and Event Grid

c. Service Bus, Event Hub, messaging and queueing technologies

d. API Management and integration technologies

e. Azure DevOps pipelines and repositories

- Guide teams in adopting AI-powered observability and anomaly detection tooling to enhance monitoring of distributed payment systems.

- Promote AI-driven insights for :

a. Capacity planning

b. Cost optimisation

c. Performance trend analysis

- Ensure AI-enabled tooling is used responsibly and aligned to governance standards.

- Lead engineering delivery across domestic, cross-border, real-time, and batch payments.

- Ensure robust support for reconciliation, exception handling, routing logic, and operational monitoring.

- Encourage the use of AI-supported analytics for identifying payment flow anomalies, operational bottlenecks, and fraud indicators (in partnership with Fraud and Risk teams).

- Partner with business, operations, compliance, and risk teams to ensure payment integrity and regulatory compliance.

Technical Experience :

- Proven experience leading engineers in complex, mission-critical environments (ideally financial services or payments).

- Extensive experience designing and delivering solutions on Microsoft Azure.

- Experience with or exposure to AI-assisted software development tools and modern AI-enabled engineering workflows.

- Deep understanding of distributed systems, observability, and high-availability architecture.