Sr. Solutions Architect, Generative AI Startups, AWS

$138,200 - $239,000/Yr

Amazon - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Sr. Solutions Architect for Generative AI Startups at AWS is responsible for guiding early-stage life sciences startups in leveraging AWS technology to develop and deploy generative AI solutions. This role involves working closely with customers to help them make informed technical decisions, architect scalable solutions, and build lasting relationships within the startup ecosystem. The position emphasizes the importance of understanding customer needs and advocating for the right AWS products and features to support their growth.

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 in solving technical problems and reducing time-to-market.

Requirements

• 3+ years of specific technology domain areas experience (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
• 3+ years of design, implementation, or consulting in applications and infrastructures experience.
• 5+ years of infrastructure architecture, database architecture, and networking experience.
• Experience working with end user or developer communities.
• Experience working with Python and generative AI libraries and frameworks such as PyTorch, JAX, TensorFlow.
• Understanding of technical details and techniques used in tuning generative AI foundation models using techniques like RAG, PEFT, RLHF, DPO.
• Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker.
• Experience with related technology areas such as distributed filesystems and high-performance networking.

Nice-to-haves

• Experience in the life sciences sector.
• Familiarity with AWS services and architecture best practices.

Benefits

• Flexible schedule
• Work-life balance
• Mentorship and career growth opportunities
• Diversity and inclusion programs