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Amazon

Principal Solutions Architect, Generative AI Startups, AWS

Amazon, San Francisco, CA, United States

Principal Solutions Architect, Generative AI Startups, AWS

Job ID: 2824225 | Amazon Web Services, Inc.

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.

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 challenge the status quo. They seek to address underserved customers, or to challenge incumbents. They usually operate in an environment of scarcity: whether that’s capital, engineering resource, or experience. This is where you come in.

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.

As well as spending time working directly with customers, you’ll also get plenty of time to learn new technologies and keep your skills fresh. We have 200+ services across a range of different categories and it’s important that we can help startups take advantages of the right ones. You’ll also play an important role as an advocate with our product teams to make sure we are building the right products and features for the startups you work with. And for the customers you don’t get to work with on a 1:1 basis you’ll share knowledge more broadly by working on technical content and presenting at events.

Key job responsibilities

  1. Help a diverse range of generative AI-focused startups to adopt the right architecture at each part of their lifecycle
  2. Support startups in architecting scalable, reliable and secure solutions
  3. Support adoption of a broad range of AWS services to deliver business value and accelerate growth
  4. Support the evolution and roadmap of the AWS platform and services, connecting our engineering teams with our customers for feedback
  5. Establish and build technical relationships within the startup ecosystem, including accelerators, incubators and VCs
  6. Develop startup specific technical content, such as blog posts, sample code and solutions, to assist customers solve technical problems and reduce time-to-market

A day in the life

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. To address underserved customers or to challenge incumbents. They usually operate in an environment of scarcity: whether that's capital, engineering resource, or experience. This is where you come in.

The AWS Startup Solutions Architecture team is dedicated to working with startup companies as they build their businesses. We're here to help them deploy the best, most scalable, most secure, cost effective and easy to operate architectures.

About the team

Diverse Experiences
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.

Why AWS

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 why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

  1. 10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
  2. Bachelor's degree in computer science, engineering, mathematics or equivalent
  3. Experience communicating across technical and non-technical audiences and at C-level, including training, workshops, publications

PREFERRED QUALIFICATIONS

  1. Knowledge of presentations and whiteboarding skills with a high degree of comfort speaking with internal and external executives, IT management, and developers
  2. Experience architecting, migrating, transforming or modernizing customer requirements to the cloud
  3. 5+ years of infrastructure architecture, database architecture and networking experience
  4. Experience working with end user or developer communities
  5. Experience working with Python and generative AI libraries and frameworks such as PyTorch, JAX, TensorFlow
  6. Understanding of technical details and techniques used in tuning generative AI foundation models using techniques like RAG, PEFT, RLHF, DPO
  7. Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker
  8. Experience with related technology areas such as distributed filesystems and high performance networking

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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