GenAI/ML Solutions Architect, Enterprise

Amazon Web Services (AWS); Seattle (WA); On-site; USD 131,000 - 204,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Job summary

AWS Global Sales seeks a GenAI/ML Solutions Architect to partner with field sales and engineering teams across the US. You will design end-to-end GenAI architectures, agentic AI workflows, and production-scale inference pipelines using Bedrock, Bedrock AgentCore, SageMaker AI, and Nova models.

You will create reference implementations, workshops, and blogs to help customers accelerate AI adoption while collaborating with product teams to drive improvements based on customer feedback.

Qualifications

• 4+ years of experience in technology domains (software/cloud/infrastructure)
• Hands-on experience with foundation models, RAG pipelines, and prompt engineering
• Familiarity with GenAI ecosystem, evaluation tools and orchestration frameworks

Responsibilities

• Work with customers' development, data science, and AI engineering teams to design solutions using AWS GenAI/ML services
• Partner with AWS teams to accelerate customer adoption and revenue attainment in AMERICAS for GenAI/ML services
• Evangelize GenAI/ML services through blogs, reference architectures, and public events
• Liaise between customers and AWS service teams to provide feedback and feature requests
• Develop internal GenAI experts and enable field teams to position opportunities

Skills

4+ years of domain experience

2+ years design/implementation/consult

Tools

Amazon Bedrock

AgentCore

SageMaker AI

Nova models

Kiro

Job description

AWS Global Sales seeks a GenAI/ML Solutions Architect to partner with field sales and engineering teams across the US. You will design end-to-end GenAI architectures, agentic AI workflows, and production-scale inference pipelines using Bedrock, Bedrock AgentCore, SageMaker AI, and Nova models.

You will create reference implementations, workshops, and blogs to help customers accelerate AI adoption while collaborating with product teams to drive improvements based on customer feedback.