Embedded AI Solutions Architect for Agentic WorkSpaces

Amazon Web Services (AWS); Seattle (WA); On-site; USD 154,000 - 208,000; Full time

Job summary

Amazon Web Services, Inc. seeks a hands‑on Solutions Architect for the Agentic WorkSpaces program. You will embed with customers, co‑design AI agent solutions, and drive production deployments of agentic AI across desktop environments.

You will leverage MCP and tool integrations, build serverless workflows, and ensure data readiness for AI agents while collaborating with customer engineering teams to reach production readiness at scale.

Qualifications

• 7+ years of experience across software development, cloud computing, and related infrastructure.
• 3+ years designing/implementing or consulting on applications and infrastructures.
• Experience with one of the following languages: Python, Ruby, Node.js, C#, or C++.

Responsibilities

• Lead technical discovery sessions with customer teams to understand requirements and translate findings into actionable deployment plans.
• Design and configure agentic AI solutions within Agentic WorkSpaces, including agent creation, prompts, and tool integrations.
• Build serverless integrations using AWS Lambda, API Gateway, Step Functions, and scripting (Python, Node.js).
• Architect secure access patterns to cloud data systems (DynamoDB, RDS, S3) to power AI agents and RAG.
• Help customers deploy WorkSpaces as the delivery platform for agentic AI experiences.
• Create reusable artifacts (reference architectures, implementation guides, sample code) for scale across SA community.

Skills

Python

Node.js

C++

Agentic AI patterns

MCP protocol

Tools

Amazon Bedrock

Lambda

API Gateway

Step Functions

Job description

Amazon Web Services, Inc. seeks a hands‑on Solutions Architect for the Agentic WorkSpaces program. You will embed with customers, co‑design AI agent solutions, and drive production deployments of agentic AI across desktop environments.

You will leverage MCP and tool integrations, build serverless workflows, and ensure data readiness for AI agents while collaborating with customer engineering teams to reach production readiness at scale.