Amazon
Principal Solutions Architect, Generative AI Startups, AWS
Amazon, New York, New York, us, 10261
Do you like startups? Are you an expert in the development and practical application of deep learning and generative AI? Are you interested in the intersection of cloud computing, generative AI, and disrupting innovation? Yes? We have a role you might find interesting.
We are looking for technical builders who love the idea of working with early stage life sciences startups to help them as they grow. In this role, you’ll work directly with a variety of interesting life sciences customers (such as drug discovery, next gen sequencing, and diagnostics startups) and help them make the best (and sometimes the most pragmatic) technical decisions along the way. You’ll have a chance to build enduring relationships with these companies and establish yourself as a trusted advisor.
As a member of the Generative AI Startups team, you will work directly with customers to help them successfully leverage cutting-edge AWS technology to develop, train, tune, and deploy the next generation of generative AI foundation models at scale.
Key job responsibilities:
Help a diverse range of generative AI-focused startups to adopt the right architecture at each part of their lifecycle.
Support startups in architecting scalable, reliable and secure solutions.
Support adoption of a broad range of AWS services to deliver business value and accelerate growth.
Support the evolution and roadmap of the AWS platform and services, connecting our engineering teams with our customers for feedback.
Establish and build technical relationships within the startup ecosystem, including accelerators, incubators and VCs.
Develop startup specific technical content, such as blog posts, sample code and solutions, to assist customers solve technical problems and reduce time-to-market.
Minimum Requirements:
10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
Bachelor's degree in computer science, engineering, mathematics or equivalent.
Experience communicating across technical and non-technical audiences and at C-level, including training, workshops, publications.
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We are looking for technical builders who love the idea of working with early stage life sciences startups to help them as they grow. In this role, you’ll work directly with a variety of interesting life sciences customers (such as drug discovery, next gen sequencing, and diagnostics startups) and help them make the best (and sometimes the most pragmatic) technical decisions along the way. You’ll have a chance to build enduring relationships with these companies and establish yourself as a trusted advisor.
As a member of the Generative AI Startups team, you will work directly with customers to help them successfully leverage cutting-edge AWS technology to develop, train, tune, and deploy the next generation of generative AI foundation models at scale.
Key job responsibilities:
Help a diverse range of generative AI-focused startups to adopt the right architecture at each part of their lifecycle.
Support startups in architecting scalable, reliable and secure solutions.
Support adoption of a broad range of AWS services to deliver business value and accelerate growth.
Support the evolution and roadmap of the AWS platform and services, connecting our engineering teams with our customers for feedback.
Establish and build technical relationships within the startup ecosystem, including accelerators, incubators and VCs.
Develop startup specific technical content, such as blog posts, sample code and solutions, to assist customers solve technical problems and reduce time-to-market.
Minimum Requirements:
10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
Bachelor's degree in computer science, engineering, mathematics or equivalent.
Experience communicating across technical and non-technical audiences and at C-level, including training, workshops, publications.
#J-18808-Ljbffr