AI Engineer

Barclays is seeking an AI Engineer, AVP to build and deploy AI and GenAI capabilities that can be used in production settings. The role focuses on using data analytics and machine learning to uncover insights from the bank’s data, support strategic decision-making, and advance innovation across the organisation.

This contract position is based in Henderson, NV on site, with a salary range of USD 165,755 to 175,000 per year.

What you will do

• Build and deploy AI/GenAI applications including Retrieval-Augmented Generation (RAG), conversational AI, and agentic workflows, along with intelligent automation solutions.
• Design and develop scalable backend services, APIs, and integrations that connect AI models with enterprise data platforms and business applications.
• Architect and manage cloud-native AI workloads running on containerized platforms such as Kubernetes and Amazon EKS.
• Develop and maintain CI/CD pipelines, infrastructure-as-code, model deployment frameworks, monitoring, and operational telemetry.
• Design secure networking solutions including VPC architecture, private connectivity, load balancing, service-to-service communication, API gateways, DNS, and network security controls.
• Optimize AI application performance, scalability, availability, and cost efficiency across computing, storage, and networking layers.
• Implement MLOps/LLMOps practices such as model versioning, automated testing, deployment, observability, rollback, and lifecycle management.
• Partner with business and technology stakeholders to deploy production-ready AI capabilities while meeting governance, security, and audit requirements.
• Identify, collect, and extract data from internal and external sources.
• Perform data cleaning, wrangling, and transformation to ensure data quality and suitability for analysis.
• Develop and maintain data pipelines for automated data acquisition and processing.
• Design and conduct statistical and machine learning models to analyze patterns, trends, and relationships.
• Develop and implement predictive models to forecast outcomes and identify risks and opportunities.
• Collaborate with business stakeholders to find ways to add value from data through Data Science.
• Advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness.
• Lead team delivery of complex tasks by setting objectives, coaching employees, assessing performance against objectives, and determining reward outcomes.
• Demonstrate the People Leader LEAD behaviours: L Listen and be authentic, E Energise and inspire, A Align across the enterprise, D Develop others.
• For an individual contributor route: lead collaborative assignments, guide team members through structured work, determine when additional specialisms are needed, and identify new directions for assignments or projects.
• Consult on complex issues, provide advice to People Leaders for escalated issues, and contribute to risk mitigation through policies and procedures aligned to control and governance.
• Take ownership for managing risk and strengthening controls related to the work performed.
• Perform closely related work requiring understanding of how sub-function areas coordinate toward organisational objectives.
• Collaborate with other areas to stay aligned with business activity and strategy.
• Conduct complex analysis of data from multiple internal and external sources to solve problems creatively and effectively.
• Communicate complex information and influence stakeholders to achieve outcomes.

Technologies

• Retrieval-Augmented Generation (RAG)
• Kubernetes
• Amazon EKS
• CI/CD pipelines
• Infrastructure-as-code
• VPC architecture
• API gateways
• DNS
• MLOps
• LLMOps
• Model versioning
• Observability
• Rollback

Benefits

• Eligible for incentives pursuant to the Barclays Employee Referral Program.

Purpose of the role

Use innovative data analytics and machine learning to extract valuable insights from the bank’s data reserves. Apply those insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.