Senior GenAI Solutions Architect, Startups

Senior GenAI Solutions Architect, Startups

Sales, Marketing and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

Do you like startups? Are you interested in Cloud Computing & Generative AI? Yes? We have a role you might find interesting. Startups are the large enterprises of the future. These young companies are founded by ambitious people who have a desire to build something meaningful and to challenge the status quo.

The Startup Solutions Architecture team is dedicated to working with these early stage startup companies as they build their businesses. We’re here to make sure that they can deploy the best, most scalable, and most secure architectures possible – and that they spend as little time and money as possible doing so.

We are looking for technical builders who love the idea of working with early stage startups to help them as they grow. In this role, you’ll work directly with a variety of interesting customers and help them make the best (and sometimes the most pragmatic) technical decisions along the way.

As well as spending time working directly with customers, you’ll also get plenty of time to “sharpen the saw” and keep your skills fresh. We have more than 175 services across a range of different categories and it’s important that we can help startups take advantages of the right ones.

A day in the life: You’re surrounded by innovation. You’re empowered with a lot of ownership. Your growth is accelerated. The work is challenging. You have a voice here and are encouraged to use it.

Basic Qualifications

Requirements:

• 8+ years of specific technology domain areas experience
• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 10+ years of IT development or implementation/consulting in the software or Internet industries experience

Preferred Qualifications

Preferred:

• Experience in developing and deploying large scale machine learning or deep learning models and/or systems into production
• Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker
• Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.