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

Amazon is hiring a Frontier AI Technical Account Manager (Germany), Enterprise Support EMEA - Startups in Berlin, Germany. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include AWS, GPU and fine tuning.
Level classifies it as a senior role.
Level lists 21,000+ other open roles at Amazon.

AI in this role

Provide technical advisory and architecture guidance to enterprise customers building frontier AI workloads and LLM pipelines on AWS.

awsgpu

fine-tuningcloud-computingmachine-learning-infrastructuredistributed-systemslarge-language-modelsgenerative-ai

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.

Basic qualifications

- 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

Preferred qualifications

- 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.

m/w/d

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Frontier AI Technical Account Manager (Germany), Enterprise Support EMEA - Startups at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Frontier AI Technical Account Manager (Germany), Enterprise Support EMEA - Startups is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in DE, BE, Berlin.
The job was posted on October 1, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningCloud ComputingMachine Learning InfrastructureDistributed SystemsLarge Language ModelsGenerative AIAWSGPU

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where cloud computing was part of your work. What did you do?
Tell me about a project where machine learning infrastructure was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where large language models was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, Cloud Computing, Machine Learning Infrastructure, Distributed Systems, and Large Language Models. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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