AI Engineering Lead

The AI Engineering Lead will spearhead the evolution of ML and AI infrastructure, platform services and deployment pipelines across the organisation. This leadership role combines hands-on technical direction with management of high-performing engineering teams, ensuring robust, scalable and secure delivery of digital solutions. The position partners closely with business, security and architecture stakeholders to align technical decisions with strategic objectives.

This is a leading global financial services organisation operating at significant scale across banking and financial markets. The company is committed to innovation in digital and technology, using advanced AI and cloud infrastructure to deliver secure, reliable services to millions of customers. Its culture is built on integrity, service, excellence and a strong sense of responsibility.

Responsibilities

• Lead and manage engineering teams, fostering a collaborative, high-performance culture aligned to organisational goals
• Design, build and maintain AWS platforms supporting AI workloads including ML and GenAI systems
• Oversee delivery timelines, team allocation, risk management and task prioritisation within scope, time and budget
• Mentor team members, conduct performance reviews and support professional growth
• Evaluate and enhance engineering processes, tools and methodologies to improve efficiency and productivity
• Enforce technology standards, lead peer reviews and implement robust testing practices
• Partner with business stakeholders, product managers and designers to translate requirements into technical solutions

Requirements

• 16-25 years of relevant experience in engineering and technology leadership
• Hands-on expertise in designing, building and maintaining AWS platforms for AI workloads
• Experience with CI/CD pipelines and Infrastructure as Code (IaC) based deployments
• Proven experience building high-performance technical teams and leading engineering teams
• Experience working across security, governance and architecture in complex enterprise environments
• Adopts a product-oriented approach focused on scalability, self-service and user experience
• Comfort with AI developer tools such as Claude Code, applying reusable patterns to accelerate development
• Practical experience building ML models and developing GenAI applications (desirable)
• Experience working in Agile environments (desirable)

Skills

AWS platform design and maintenance for AI workloads, ML and GenAI infrastructure, CI/CD pipelines, Infrastructure as Code (IaC), Building high performance technical teams, Engineering team leadership and mentorship, Security and governance in enterprise environments, Building ML models, Developing GenAI applications, Agile methodologies, AI developer tools such as Claude Code