Description
We are seeking an AI Engineering Lead - Vice President to spearhead the evolution of our ML/AI infrastructure, platform services, and deployment pipelines at Barclays, driving innovation and operational excellence.
The successful candidate will harness cutting-edge technology to build and manage robust, scalable, and secure infrastructure, ensuring seamless delivery of our digital solutions.
Key Responsibilities:
- Lead engineering teams effectively, fostering a collaborative and high-performance culture to achieve project goals and meet organisational objectives.
- Oversee timelines, team allocation, risk management, and task prioritisation to ensure the successful delivery of solutions within scope, time, and budget.
- Mentor and support team members' professional growth, conduct performance reviews, provide actionable feedback, and identify opportunities for improvement.
- Evaluate and enhance engineering processes, tools, and methodologies to increase efficiency, streamline workflows, and optimise team productivity.
- Collaborate with business partners, product managers, designers, and other stakeholders to translate business requirements into technical solutions and ensure a cohesive approach to product development.
- Enforce technology standards, facilitate peer reviews, and implement robust testing practices to ensure the delivery of high-quality solutions.
Vice President Expectations:
- Contribute to or set strategy, drive requirements, and make recommendations for change.
- Plan resources, budgets, and policies; manage and maintain policies/processes; deliver continuous improvements and escalate breaches of policies/procedures.
- Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work of your team.
- Demonstrate comprehensive understanding of the organisation's functions to contribute to achieving the goals of the business.
Requirements:
- Hands-on expertise in designing, building, and maintaining AWS platforms supporting AI workloads (ML, GenAI, agentic systems), exposure to CI/CD pipelines and IAC-based deployments.
- Proven experience working across security, governance, architecture, and business stakeholders, navigating complex enterprise environments.
- A product-oriented approach, with a focus on outcomes, scalability, self-service capabilities, continuous evolution, and exceptional user experience.
- Experience building high-performance technical teams.
- Comfortable with AI tools like Claude code and similar, applying structured rules, skills, and reusable patterns to accelerate development.
Nice to Have:
- Practical experience building ML models and developing GenAI applications.
- Experience working in Agile environments, collaborating iteratively and delivering incremental value.