GenAI/ML Solutions Architect for RAG & Agentic AI

Amazon Web Services (AWS); San Francisco (CA); On-site; USD 177,000 - 239,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Paid time off

Job summary

Amazon Web Services, Inc. seeks a GenAI/ML Solutions Architect to help US customers design and adopt GenAI and ML solutions on AWS. You will work alongside field sales to architect solutions using Bedrock, SageMaker AI, and related AI/ML services, crafting architectures for RAG pipelines and agent-based workflows.

You will collaborate with service teams, develop reference implementations, and drive customer adoption across multiple industries while contributing to technical blogs and workshops.

Qualifications

• Deep technical experience with generative AI, ML, or DL.
• Hands-on with foundation models (RAG, agent frameworks, prompt engineering, evaluation, fine-tuning).
• Strong mathematics and statistics background.
• Familiar with GenAI ecosystem and evaluation tools.
• Experience designing production ML systems.

Responsibilities

• Design GenAI/ML solutions using AWS AI/ML services including Bedrock, Bedrock AgentCore, SageMaker AI, Nova models, and related tools.
• Collaborate with field sales teams to accelerate customer adoption and revenue in the AMERICAS.
• Publish blogs, reference architectures, and demos to enable customer use of GenAI on AWS.
• Serve as technical liaison to GenAI/ML service teams for product feedback and improvements.
• Build an internal GenAI expert community across the AMERICAS.

Skills

GenAI/ML

Foundation models

RAG pipelines

Agent frameworks

Prompt engineering

Math & stats

Solution architecture

Production ML

Tools

Amazon Bedrock

Bedrock AgentCore

SageMaker AI

Nova models

Job description

Amazon Web Services, Inc. seeks a GenAI/ML Solutions Architect to help US customers design and adopt GenAI and ML solutions on AWS. You will work alongside field sales to architect solutions using Bedrock, SageMaker AI, and related AI/ML services, crafting architectures for RAG pipelines and agent-based workflows.

You will collaborate with service teams, develop reference implementations, and drive customer adoption across multiple industries while contributing to technical blogs and workshops.