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Amazon Web Services (AWS) seeks an Enterprise Account Engineer II to serve as a trusted technical advisor to customers building Frontier AI workloads on the cloud, guiding architecture, operational readiness, and performance optimization.
You will design cloud architectures for large-scale model training and inference, collaborating with solutions architects and account managers to accelerate AI initiatives while ensuring reliability and cost efficiency.
Are you passionate about helping organizations push the boundaries of artificial intelligence? As an Enterprise Account Engineer II at Amazon Web Services (AWS), you will serve as a trusted technical advisor to customers building and scaling Frontier AI workloads on the cloud. Your deep understanding of cloud computing architecture, machine learning infrastructure, and large-scale distributed systems will help customers navigate complex challenges — from training foundation models to deploying inference endpoints at scale.
You will craft and execute strategies that accelerate your customers' AI initiatives, advising on architecture, operational readiness, and performance optimization. Whether your customers are training large language models, building generative AI applications, or scaling GPU-intensive compute clusters, you will be the technical expert they rely on to achieve their goals. This is an opportunity to work at the intersection of cloud technology and AI innovation, where your recommendations directly shape how customers build the next generation of intelligent systems.
You start your morning reviewing operational health dashboards for your customers' AI training clusters, checking for scaling events or service advisories that may need attention. Mid-morning, you join an architecture review with a customer's ML engineering team to evaluate their plan for deploying a new foundation model into production. After lunch, you collaborate with an AWS service team to advocate for a feature request that would improve your customer's GPU utilization. Later, you prepare a quarterly business review that highlights progress on cloud maturity milestones and recommends next steps for optimizing their inference workloads.
Our team partners with customers who are at the forefront of AI innovation, helping them build and operate large-scale machine learning systems on AWS. We work closely with service teams, solutions architects, and account managers to deliver a unified support experience. We are growing to meet increasing demand as more organizations invest in generative AI and foundation model development, and we are looking for collaborative, curious engineers who want to help shape how AI workloads run in the cloud.
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