Applied AI Solutions Architect - Agentic WorkSpaces

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

Benefits offered by this job

Health insurance

RSUs and sign-on bonus

Paid time off and parental leave

Job summary

Amazon Web Services, Inc. is seeking an experienced Solutions Architect to embed with customers and accelerate production deployments of agentic WorkSpaces AI.

You will design, implement, and validate multi-agent AI workflows, tool integrations, and MCP/A2A patterns while working hands-on with customer engineering teams. The role requires deep expertise in desktop infrastructure, VDI/DaaS, and cloud-native architectures, with travel up to 25–40% for on-site engagements.

Qualifications

• 7+ years in software/cloud/infra domains.
• Hands-on with Python, Node.js, C#, or C++.
• Experience with agentic AI patterns and MCP/A2A interoperability.
• Familiarity with AWS Bedrock or equivalent foundation models.

Responsibilities

• Lead technical discovery sessions with customer teams to translate requirements into implementation plans.
• Design and configure agentic AI solutions within Agentic WorkSpaces, including AI agents and prompt engineering.
• Build serverless integrations using AWS Lambda, API Gateway, Step Functions and scripting (Python, Node.js).
• Architect secure access patterns to cloud-based data systems powering AI agent tools and RAG workflows.
• Collaborate with customers to deploy WorkSpaces platforms for production AI experiences.
• Create reusable artifacts and contribute to team knowledge bases.
• Provide Voice-of-Customer feedback to product teams to influence roadmaps.

Skills

Python

Node.js

C#

C++

Cloud computing

AI patterns

Tools

AWS Lambda

API Gateway

Step Functions

Bedrock

Knowledge bases

RAG

Job description

Amazon Web Services, Inc. is seeking an experienced Solutions Architect to embed with customers and accelerate production deployments of agentic WorkSpaces AI.

You will design, implement, and validate multi-agent AI workflows, tool integrations, and MCP/A2A patterns while working hands-on with customer engineering teams. The role requires deep expertise in desktop infrastructure, VDI/DaaS, and cloud-native architectures, with travel up to 25–40% for on-site engagements.