Frontier AI Technical Account Manager
Amazon
Frontier AI Technical Account Manager
Amazon
Sells products online and rents cloud computing
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.
Key job responsibilities
- Design and recommend cloud architectures optimized for Frontier AI workloads, including large-scale model training, fine-tuning, and inference across GPU and accelerator-based compute environments
- Drive technical discussions on operational trade-offs, incident management, and risk mitigation for customers running complex AI and machine learning pipelines on AWS
- Collaborate with solutions architects, service engineering teams, and account managers to identify adoption opportunities and resolve technical blockers for AI-focused customers
- Review customer environments proactively to improve resilience, scalability, and cost efficiency, ensuring their AI infrastructure meets performance and availability targets
- Deliver technical guidance through architecture reviews, workshops, and enablement sessions that help customers integrate cloud and AI best practices into their operational processes
A day in the life
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.
About the team
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.
- Experience with operational parameters and troubleshooting for three (3) of the following: compute/storage/networking/CDN/databases/DevOps/big data and analytics/security/applications development in a distributed systems environment
- Experience in technical engineering
- Experience with AWS services or other cloud offerings
- Experience in internal enterprise or external customer-facing environment as a technical lead
- Bachelor's degree or equivalent
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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