Sr. Startup Solution Architect, Genai

Amazon Amazon · Big Tech · DIF, Mexico +1 · Solutions Architect

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models at scale. The individual will act as a trusted advisor, architecting solutions, supporting adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events.

What you'd actually do

  1. Help a diverse range of generative AI-focused startups to develop, train and 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

Skills

Required

  • 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) 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
  • Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM), or experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
  • Business Communication in English and Spanish

Nice to have

  • 5+ years of infrastructure architecture, database architecture and networking experience
  • Experience working with end user or developer communities

What the JD emphasized

  • development and tuning of models
  • practical application of GenAI
  • generative AI foundation models at scale

Other signals

  • customer facing
  • startup ecosystem
  • generative AI foundation models
  • AWS technology