AI Engineer

What you’ll do: Build and deploy AI/GenAI applications including Retrieval-Augmented Generation (RAG), conversational AI, agentic workflows, and intelligent automation solutions. Design scalable backend services, APIs, and integrations that connect AI models with enterprise data platforms and business applications. Architect and manage cloud-native AI workloads on containerized platforms, including Kubernetes and Amazon EKS. Develop and maintain CI/CD pipelines, infrastructure-as-code, model deployment frameworks, monitoring, and operational telemetry. Implement 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. Apply MLOps/LLMOps practices such as model versioning, automated testing, deployment, observability, rollback, and lifecycle management. Partner with business and technology stakeholders to deliver production-ready AI capabilities while adhering to governance, security, and audit requirements. Data and model work Identify, collect, and extract data from internal and external sources. Perform data cleaning, wrangling, and transformation to ensure data quality and analysis readiness. Design and maintain data pipelines for automated data acquisition and processing. Design and conduct statistical and machine learning modeling to analyze patterns, trends, and relationships. Develop and implement predictive models to forecast outcomes and identify risks and opportunities. Collaborate with stakeholders to find ways to add value from data through Data Science. Influence, delivery, and leadership Advise and influence decision-making, contribute to policy development, and take responsibility for operational effectiveness in collaboration with other functions and business divisions. Lead complex work impacting the whole business function by setting objectives, coaching employees, and supporting performance appraisal and reward outcomes. Model leadership behaviors aligned to LEAD: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others. If acting as an individual contributor, lead collaborative assignments and guide team members through structured work, including coordinating cross-functional specialisms. Consult on complex issues and provide advice to People Leaders for escalated issue resolution. Identify ways to mitigate risk, develop policies and procedures for control and governance, and strengthen controls through risk ownership. Engage in complex analysis across multiple internal and external information sources, communicate complex information when needed, and influence stakeholders to achieve outcomes. Technologies you may use Retrieval-Augmented Generation (RAG), Kubernetes, Amazon EKS CI/CD pipelines, infrastructure-as-code, VPC architecture API gateways, DNS, MLOps, LLMOps Model versioning, observability, rollback Compensation and eligibility Salary: USD $165,755 - $175,000 per year. The position is eligible for incentives pursuant to the Barclays Employee Referral Program.