GenAI/ML Solutions Architect for Enterprise AI

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

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a GenAI/ML Solutions Architect to help US customers design applied AI solutions using AWS Bedrock, Bedrock AgentCore, SageMaker AI, and Nova models. You will work with field sales teams across verticals, architecting RAG pipelines and production-scale inference while advising on responsible AI and model customization.

You will develop workshops, reference implementations, and blogs to enable customers to accelerate AI adoption, collaborating with service teams to drive product

Qualifications

• 8+ years of experience in technology domains such as software, cloud, systems engineering, infrastructure, security, or data & analytics.
• 3+ years of design, implementation, or consulting in applications and infrastructures.
• Experience in a technical role within a sales organization.

Responsibilities

• Design GenAI/ML solutions leveraging AWS AI/ML services for diverse customers.
• Partner with SAs, Sales, and AI/ML teams to drive adoption and revenue in the AMERICAS.
• Evangelize AWS GenAI/ML services via blogs, whitepapers, reference architectures, and events.
• Serve as liaison between customers and AI service teams to feedback features.
• Develop internal GenAI SME community across the AMERICAS for opportunity positioning.
• Spend most time with customers to solve real business problems using GenAI/ML.

Skills

GenAI/ML

RAG pipelines

Agentic AI

Prompt engineering

ML production systems

Architecting AI solutions

Tools

AWS Bedrock

Bedrock AgentCore

SageMaker AI

Nova foundation models

Amazon Quick

Kiro

Rekognition

Textract

Transcribe

Job description

Amazon is seeking a GenAI/ML Solutions Architect to help US customers design applied AI solutions using AWS Bedrock, Bedrock AgentCore, SageMaker AI, and Nova models. You will work with field sales teams across verticals, architecting RAG pipelines and production-scale inference while advising on responsible AI and model customization.

You will develop workshops, reference implementations, and blogs to enable customers to accelerate AI adoption, collaborating with service teams to drive product