Lead AI/ML Solutions

Lead a multidisciplinary engineering team and take end-to-end accountability for the strategy, architecture, delivery, governance, production adoption and continuous improvement of secure, governed and measurable agentic AI solutions.
•    Set the engineering direction and translate business, risk, compliance and regulatory needs into scalable solution designs. Guide implementation of orchestration, tool calling, retrieval, memory, workflow automation, human-in-the-loop controls, sandboxed execution and enterprise integrations, while ensuring security, reliability, resilience, observability, auditability and production readiness.
•    Own execution from discovery through build, testing, release, adoption and support. Lead and develop engineers, establish standards for code quality, automated testing and evaluation, manage delivery and technology risks, embed responsible AI and control requirements, engage senior stakeholders, monitor operational and business outcomes, and build reusable patterns and AI-assisted SDLC accelerators that improve quality, consistency and delivery speed.

Engineering strategy and architecture
•    Define and execute the engineering strategy, technical direction, solution design principles and roadmap for governed agentic AI capabilities across the AI/ML delivery portfolio.
•    Design and guide implementation of orchestration, tool calling, retrieval, memory, workflow automation, enterprise integration, human-in-the-loop controls and sandboxed execution patterns.

End-to-end delivery and business outcomes
•    Own delivery from intake and discovery through design, build, test, release, production adoption, support and continuous improvement, with clear accountability for scope, quality, timelines and value.
•    Partner with business, product, risk, compliance and technology stakeholders to agree priorities, outcomes, dependencies, controls and adoption requirements.

Engineering excellence and production readiness
•    Establish standards for code quality, design reviews, documentation, peer review, automated testing, prompt and model evaluation, release controls, traceability and evidence capture.
•    Ensure production readiness across security, reliability, scalability, resilience, observability, telemetry, support, incident response, rollback and operational handover.

Risk, responsible AI and governance
•    Own identification, assessment, mitigation and escalation of delivery, technology, security, data, model, operational and regulatory risks.
•    Embed responsible AI, model risk, data protection, access control, approval, auditability and governance controls, and provide evidence-based updates to decision forums.

Continuous improvement and reusable capability
•    Monitor adoption, performance, evaluation results, control effectiveness, incidents and business outcomes, using evidence to drive remediation and product evolution.
•    Create reusable engineering patterns, platforms and accelerators, including AI-assisted SDLC practices that improve productivity, consistency and speed without compromising control.
    
People and Talent 
•    Set direction and drive high performance by translating strategy into clear direction, aligning individual goals to team outcomes and providing regular, constructive feedback.
•    Develop talent and capability through coaching and career conversations that build critical skills, stretch potential and prepare individuals for future opportunities.
•    Lead by example by role-modelling the Bank’s valued behaviours, upholding strong risk and conduct standards, exercising sound judgment, and creating an inclusive team culture that supports wellbeing, values diverse perspectives, and drives accountability.
•    Lead, manage and develop engineering teams by setting direction, clarifying priorities, allocating work, coaching engineers and creating a high-accountability, collaborative delivery culture.
•    Build capability through hiring, onboarding, mentoring, career development, knowledge sharing, cross-skilling, succession planning and clear ownership of critical solutions.