Team Lead, Digital Innovation And Design

Key Responsibilities

• This role requires the incumbent to be a hands-on software engineering technologist who actively designs, writes, reviews, and deploys production-grade code. It is not a pure product, UX, or project management role
• Lead the design and implementation of AI-first and agentic AI-driven solutions, including LLM integration, autonomous workflows, and AI-driven decision capabilities embedded within enterprise systems
• Act as a hands-on software engineering lead, actively designing, coding, and delivering scalable, production-grade digital solutions across web, mobile, AI, and enterprise platforms
• Design and own scalable system architectures, ensuring robustness, security, performance, and maintainability across applications and integrations
• Develop, review, and optimise high-quality production code, APIs, automation scripts, and integrations, adhering to strong engineering and clean code principles
• Collaborate closely with engineering teams to solve complex technical challenges, contributing directly through coding, debugging, and architectural refinement
• Leverage modern engineering stacks and platforms to deliver scalable solutions, with familiarity in integrating enterprise platforms (e.g. Microsoft Power Platform) where appropriate
• Define and implement DevSecOps practices, embedding security-by-design across CI/CD pipelines and driving automation, testing, and deployment excellence
• Mentor and guide engineers through active technical contribution, setting standards in coding, architecture, and engineering discipline
• Drive end-to-end technical delivery, including architecture decisions, system dependencies, and execution aligned with business priorities
• Translate business and user needs into scalable, AI-enabled technical solutions, ensuring iterative delivery, continuous improvement, and measurable impact

Requirement

Skills

• Strong hands-on software engineering capability with the ability to independently design, write, and review production-grade code
• Proven ability to solve complex technical problems through coding, debugging, and system design
• Clear primary background in software engineering (not product, UX, or project management)
• Strong analytical thinking and problem-solving skills with high attention to engineering quality and detail
• Effective communication skills with the ability to translate technical concepts into business impact
• Self-driven, results-oriented, and able to operate independently in a fast-paced engineering environment
• Strong collaboration and interpersonal skills, with experience working across cross-functional engineering teams

Knowledge

• Practical experience in AI-enabled solution development, including LLM integration, intelligent automation, agentic AI, and platforms such as Azure AI Foundry for building and orchestrating enterprise AI solutions
• Strong understanding of software architecture and system design principles, including scalable, distributed, and API-driven systems
• Hands-on experience with modern development stacks, including ReactJS / React Native, Node.js, Java, .NET, Python, APIs, and containerisation (e.g. Docker, Kubernetes)
• Hands-on experience with DevSecOps practices, CI/CD pipelines, automated testing, and secure software delivery
• Familiarity with integrating enterprise platforms (e.g. Microsoft Power Platform) as part of broader system architecture
• Strong understanding of Agile/Scrum methodologies in engineering delivery environments
• Domain knowledge in banking or financial services is an advantage

Experience

• Degree in Computer Science, Software Engineering, or a related technical field
• Minimum 10 years of experience in software engineering, with a strong track record in hands-on development and system design
• Recent and active hands-on coding experience is required, with proven involvement in building and deploying production systems
• Demonstrated experience in designing and delivering scalable, enterprise-grade digital platforms and systems
• Experience in building or integrating AI-enabled solutions, including LLM-based applications, intelligent automation, or agentic AI systems, is highly advantageous
• Experience in web and mobile application development using modern technology stacks
• Experience in banking, financial services, or regulated environments is an advantage, but not mandatory