GenAI/ML Solutions Architect - Cloud AI Solutions Expert

Socket.dev

Boston (MA)

On-site

USD 131,000 - 178,000

Full time

9 days ago

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Job summary

Amazon AWS is seeking a GenAI/ML Solutions Architect to design and deploy GenAI/ML solutions for customers using Bedrock, SageMaker, and Nova models in a production environment. You will work with field teams across the AMERICAS to architect, pilot, and scale real-world GenAI/ML applications.

The role requires deep technical expertise in generative AI, ML, and production ML systems, with travel up to 20–30% for customer workshops and enablement.

Qualifications

  • 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
  • 2+ years of design, implementation, or consulting in applications and infrastructures experience.

Responsibilities

  • Working with customers' development, data science, and AI engineering teams to understand needs and design solutions that use AWS GenAI/ML services.
  • Partner with SAs, Sales, BD and AI/ML teams to accelerate adoption and revenue in the AMERICAS for GenAI/ML services.
  • Thought leadership: evangelize AWS GenAI/ML services via blogs, whitepapers, reference architectures, sample code, and events.
  • Act as a technical liaison to provide customer-driven product feedback and feature requests to the Bedrock/SageMaker/AgentCore teams.
  • Develop internal GenAI SME community in the AMERICAS to help field teams position opportunities.
  • Travel up to 20–30% across the United States for workshops and briefings.

Skills

4+ years of tech/domain experience
2+ years of design/implementation/ing

Job description

Amazon AWS is seeking a GenAI/ML Solutions Architect to design and deploy GenAI/ML solutions for customers using Bedrock, SageMaker, and Nova models in a production environment. You will work with field teams across the AMERICAS to architect, pilot, and scale real-world GenAI/ML applications.

The role requires deep technical expertise in generative AI, ML, and production ML systems, with travel up to 20–30% for customer workshops and enablement.

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