Frontier AI Technical Account Manager

Frontier AI Technical Account Manager (France), Enterprise Support EMEA - Startups

Job ID: 10538464 | AWS EMEA SARL (France Branch)

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end‑to‑end products that surprise and delight out‑of‑the‑box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.

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 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

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

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's