Senior Solutions Architect – Agentic WorkSpaces AI

About the role

The Agentic WorkSpaces Solutions Architect team is seeking a hands‑on, customer‑obsessed Senior Solutions Architect to accelerate adoption of agentic AI capabilities built on Amazon WorkSpaces. You will be embedded with customers to design, build, and productionize AI‑enabled virtual desktop environments.

Key responsibilities

• Lead technical discovery sessions, translate business requirements into implementation plans, and guide customers from evaluation to production deployment.
• Design and configure agentic AI solutions, including model selection via Amazon Bedrock, prompt engineering, and tool integration.
• Build serverless integrations using AWS Lambda, API Gateway, Step Functions, and scripting in Python or Node.js.
• Architect secure access to cloud data services (DynamoDB, RDS, S3, knowledge bases) to power AI agents and retrieval‑augmented generation.
• Deploy and validate Amazon WorkSpaces (Personal, Pools, Applications) as the delivery platform for AI experiences.
• Create reusable artifacts such as reference architectures, implementation guides, sample code, and data readiness checklists.
• Provide Voice‑of‑Customer feedback to the service team and contribute to product roadmap.

Required profile

• 7+ years of experience in software development, cloud computing, systems engineering, or related technology domains.
• 3+ years designing, implementing, or consulting on applications and infrastructure, with hands‑on experience in AI/ML systems.
• Experience evaluating foundation models and working with Amazon Bedrock or equivalent platforms.
• Familiarity with interoperability protocols such as Model Context Protocol (MCP) and Agent‑to‑Agent (A2A) communication.
• Strong understanding of Virtual Desktop Infrastructure (VDI) and Desktop‑as‑a‑Service (DaaS) architectures.

Required skills

• AWS services (WorkSpaces, Bedrock, Lambda, API Gateway, Step Functions, DynamoDB, RDS, S3)
• Programming languages: Python, Node.js
• Serverless architecture and API integration
• Prompt engineering and AI model selection
• Tool integration using MCP and A2A patterns
• Knowledge of VDI/DaaS networking, identity, and operational patterns