Director of Software Engineering and ML - Agentic Commerce - Executive Director

Role overview

Leadership and delivery

• Build and lead the engineering team, with responsibility for hiring, coaching, career development and performance.
• Own the delivery roadmap from first production release through scale-out, partnering with product, programme and design teams.
• Make decisions on resources, budget, vendors and team operations; communicate progress, risks and trade-offs to senior leaders.

Technical direction and production

• Set direction for multi-agent architecture, controlled pricing and policy decisions, evaluation and observability.
• Establish production ML practices for training, testing, promotion, serving, monitoring and retraining.
• Lead model risk, cybersecurity and control reviews before launch and own production stability.
• Promote authorised AI-assisted engineering, output validation and reusable practices.

Partnerships and evaluation

• Partner with NEO, data platform, client channel and business teams, contributing reusable platform components.
• Evaluate vendors, startups and internal teams for architecture, technical credentials and fit with existing systems.
• Support a team culture of diversity, opportunity, inclusion and respect.

Required qualifications and skills

• Software engineering training or certification and advanced applied experience, including significant engineering team leadership.
• Hands-on system design, application development, testing and operational stability experience; track record building and scaling teams.
• Experience delivering production AI/ML systems and understanding of the production ML lifecycle and governance.
• Experience leading approved AI-assisted development and setting validation expectations for correctness, performance and security.
• Understanding of responsible AI, data sensitivity, secure handling, resiliency and security.
• Advanced SDLC and agile knowledge, including CI/CD, application resiliency and security; practical cloud-native experience.
• Proficiency with Kubernetes, Amazon EKS, micro-VM isolation and sidecar patterns, including security design across stack layers.
• Ability to influence across organisational boundaries and communicate with executive audiences.

Preferred experience

• Agent frameworks and protocols such as MCP, A2A, Google ADK and LangGraph, and agent evaluation practices.
• Databricks, MLflow and model serving on Kubernetes in AWS; AI delivery through model risk management or equivalent review.
• Federated platform team experience, B2B payments or related domain knowledge, or experience building a new engineering hub or team.