AI Engineer, AVP

Barclays•Henderson, NV

1d•$165,755 - $175,000•Onsite

About The Position

Barclays Services LLC seeks an AI Engineer, AVP, in Henderson, Nevada. The role uses data analytics and machine learning to extract insights from bank data and support strategic decision-making, operational efficiency, and innovation. The AI Engineer builds and deploys AI and generative AI applications, including retrieval-augmented generation (RAG), conversational AI, agentic workflows, and intelligent automation. The position also develops scalable backend services and APIs, connects AI models with enterprise data platforms and business applications, and operates cloud-native AI workloads on containerized platforms such as Kubernetes and Amazon EKS. The role builds and maintains CI/CD pipelines, infrastructure-as-code, model deployment frameworks, monitoring, and operational telemetry. It designs secure networking solutions and optimizes performance, scalability, availability, and cost efficiency across computing, storage, and networking. The AI Engineer implements MLOps/LLMOps practices and works with business and technology stakeholders to deliver production-ready AI capabilities in accordance with governance, security, and audit requirements. At the Assistant Vice President level, colleagues advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness. They collaborate across functions and business divisions, manage risk and controls, communicate complex information, and influence stakeholders. Leadership expectations include leading complex work and coaching employees where the role has people-management responsibilities; individual contributors lead collaborative assignments and guide team members through structured work. Colleagues are expected to demonstrate Barclays Values and Mindset.

Responsibilities

Build and deploy AI and generative AI applications, including RAG, conversational AI, agentic workflows, and intelligent automation solutions.
Design and develop scalable backend services, APIs, and integrations connecting AI models with enterprise data platforms and business applications.
Architect and manage cloud-native AI workloads on containerized platforms, including Kubernetes and Amazon EKS.
Build 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, including 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; clean, wrangle, and transform data for analysis.
Develop and maintain data pipelines for automated data acquisition and processing.
Design and conduct statistical and machine learning models to analyze data patterns, trends, and relationships; develop predictive models to forecast outcomes and identify risks and opportunities.
Collaborate with business stakeholders to identify opportunities to create value through data science.
Advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness.
Take ownership of risk management and strengthening controls; identify ways to mitigate risk and develop policies and procedures supporting control and governance.
Engage in complex analysis of information from multiple sources to solve problems creatively and effectively; communicate complex information and influence stakeholders.
Lead collaborative assignments and guide team members through structured assignments, where applicable.