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Senior Solutions Architect — Agentic WorkSpaces AI
Job Location:
Job Location:
Seattle, OR - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
13 August 2026 (6 hours ago)
Posted:
Application Deadline:
10 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
This position is part of the AWS Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains providing the business and technical expertise to help our customers succeed.
The Agentic WorkSpaces Solutions Architect team is seeking a hands-on customer-obsessed Solutions Architect to accelerate customer adoption of agentic AI capabilities built on Amazon WorkSpaces. This team operates as a dedicated advisory and hands-on development function assigning engineering resources directly to customers to achieve production-ready outcomes in weeks instead of months.
As an Applied AI Solutions Architect you will be embedded with customers to help them prepare their Agentic WorkSpaces implementations for production. Your work centers on three pillars of agentic AI:
- Model Selection Guiding customers through evaluating and selecting the right foundation models (via Amazon Bedrock) for their workspace use cases balancing latency accuracy cost and compliance requirements.
- Prompt Configuration Designing testing and optimizing AI prompts and system instructions for agentic workspace AI including self-service agents recommendation agents and custom orchestrator agents.
- Tool Configuration Architecting and building the tool integrations (APIs Lambda functions data connectors knowledge bases) that agentic AI systems use to take actions on behalf of users including configuring MCP (Model Context Protocol) servers for standardized tool discovery and invocation and enabling A2A (Agent-to-Agent) communication patterns for multi-agent orchestration across enterprise systems.
- A critical dimension of this role is Customer Data Readiness assessing preparing and structuring customer data assets so that AI agents can reliably access retrieve and act on the right information.
The delivery substrate for this work is Desktop Infrastructure (VDI) and Desktop-as-a-Service (DaaS). You must understand the architecture networking identity and operational patterns of virtualized desktop environments because that is where these AI agents operate and where customers derive value.
You will work at the intersection of end-user computing and applied AI helping customers move from proof-of-concept to production for their Agentic WorkSpaces deployments.
This is a deeply technical hands-on role. You will write code build integrations configure agents and pair-program with customer engineering teams.
This role operates as forward deployed engineering. You will co-build AI solutions directly alongside customer developers not hand off reference architectures and walk away. Per the Customer Deployment Engineering ) methodology you will navigate dev and test environments with the customer validate configurations under real workload conditions and identify production blockers before they surface. You will leverage these engagements to advise customers on production rollouts of WorkSpaces Agent Access transitioning validated prototypes into fully operational agentic desktop environments at scale.
Willingness to travel up to 2540% for on-site customer engagements.
Key job responsibilities
You will lead technical discovery sessions with customer teams to understand business requirements existing desktop infrastructure and AI readiness. You translate findings into actionable implementation plans that move customers from evaluation to production deployment.
You will design and configure agentic AI solutions within Agentic WorkSpaces including AI agent creation prompt engineering and tool/action integration.
You will build serverless integrations using AWS Lambda API Gateway Step Functions and scripting (Python ).
You will architect secure access patterns to cloud-based data systems (e.g. Amazon DynamoDB Amazon RDS Amazon S3 Knowledge Bases for Bedrock) to power AI agent tool use and retrieval-augmented generation (RAG).
You will work with customers to deploy Amazon WorkSpaces Personal Pools and Amazon WorkSpaces Applications as the delivery platform for agentic AI experiences.
You will guide customers through testing evaluation and validation of AI agent performance against defined success criteria before production deployment.
You will create reusable artifacts reference architectures implementation guides sample code prompt libraries data readiness checklists that scale best practices across the SA community and partner ecosystem.
You will provide Voice-of-Customer feedback to the Agentic WorkSpaces Service Team based on real-world customer implementations contributing to product roadmap prioritization.
A day in the life
You pair-program with customer developers to build and test AI agent configurations deployed on WorkSpaces environments. You design prompt strategies and evaluate model performance across different foundation models. You configure MCP servers to expose customer APIs databases and tools in a standardized format for agent consumption. You design A2A workflows where workspace agents hand off to or collaborate with specialized agents across the customers enterprise. You deploy and validate WorkSpaces architectures to ensure the desktop substrate is production-ready. You configure knowledge bases and data connectors for RAG-powered agent responses. You conduct architecture reviews and provide prescriptive guidance for production readiness. You document implementation patterns and contribute to the teams knowledge base. You participate in weekly syncs with service teams to share customer feedback and product insights.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger more collaborative teams. Our continual innovation is fueled by the bold ideas fresh perspectives and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve.
- 7 years of specific technology domain areas (e.g. software development cloud computing systems engineering infrastructure security networking data & analytics) experience
- 3 years of design implementation or consulting in applications and infrastructures experience
- Experience with one of the following programming languages: Python Ruby C# or C
- Hands-on experience with agentic AI patterns multi-agent orchestration tool use function calling chain-of-thought reasoning and autonomous agent workflows.
- Familiarity with interoperability protocols such as MCP (Model Context Protocol) for standardized tool integration and/or A2A (Agent-to-Agent) for multi-agent communication.
- Experience with Amazon Bedrock or equivalent foundation model platforms including model invocation agent creation knowledge base configuration and guardrails.
- Understanding of Virtual Desktop Infrastructure (VDI) and Desktop-as-a-Service (DaaS) technology architecture networking identity image management and operational patterns.
- 5 years of infrastructure architecture database architecture and networking experience
- Experience implementing cloud services including migrations and modernization projects or similar
- Experience working with end user or developer communities
- 5 years of experience and practical knowledge with VDI and DaaS solutions preferably Amazon WorkSpaces AppStream 2.0 Citrix or VMware/Omnissa Horizon.
- Hands-on experience building and deploying MCP servers exposing enterprise tools and APIs via Model Context Protocol for dynamic agent tool discovery and invocation.
- Hands-on experience with retrieval-augmented generation (RAG) vector databases and knowledge base configuration for production AI systems.
- AWS Solutions Architect certification (Associate or Professional) and/or AI Practitioner Certification.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The Agentic WorkSpaces Solutions Architect team is seeking a hands-on customer-obsessed Solutions Architect to accelerate customer adoption of agentic AI capabilities built on Amazon WorkSpaces. This team operates as a dedicated advisory and hands-on development function assigning engineering resources directly to customers to achieve production-ready outcomes in weeks instead of months.
As an Applied AI Solutions Architect you will be embedded with customers to help them prepare their Agentic WorkSpaces implementations for production. Your work centers on three pillars of agentic AI:
- Model Selection Guiding customers through evaluating and selecting the right foundation models (via Amazon Bedrock) for their workspace use cases balancing latency accuracy cost and compliance requirements.
- Prompt Configuration Designing testing and optimizing AI prompts and system instructions for agentic workspace AI including self-service agents recommendation agents and custom orchestrator agents.
- Tool Configuration Architecting and building the tool integrations (APIs Lambda functions data connectors knowledge bases) that agentic AI systems use to take actions on behalf of users including configuring MCP (Model Context Protocol) servers for standardized tool discovery and invocation and enabling A2A (Agent-to-Agent) communication patterns for multi-agent orchestration across enterprise systems.
- A critical dimension of this role is Customer Data Readiness assessing preparing and structuring customer data assets so that AI agents can reliably access retrieve and act on the right information.
The delivery substrate for this work is Desktop Infrastructure (VDI) and Desktop-as-a-Service (DaaS). You must understand the architecture networking identity and operational patterns of virtualized desktop environments because that is where these AI agents operate and where customers derive value.
You will work at the intersection of end-user computing and applied AI helping customers move from proof-of-concept to production for their Agentic WorkSpaces deployments.
This is a deeply technical hands-on role. You will write code build integrations configure agents and pair-program with customer engineering teams.
This role operates as forward deployed engineering. You will co-build AI solutions directly alongside customer developers not hand off reference architectures and walk away. Per the Customer Deployment Engineering ) methodology you will navigate dev and test environments with the customer validate configurations under real workload conditions and identify production blockers before they surface. You will leverage these engagements to advise customers on production rollouts of WorkSpaces Agent Access transitioning validated prototypes into fully operational agentic desktop environments at scale.
Willingness to travel up to 2540% for on-site customer engagements.
Key job responsibilities
You will lead technical discovery sessions with customer teams to understand business requirements existing desktop infrastructure and AI readiness. You translate findings into actionable implementation plans that move customers from evaluation to production deployment.
You will design and configure agentic AI solutions within Agentic WorkSpaces including AI agent creation prompt engineering and tool/action integration.
You will build serverless integrations using AWS Lambda API Gateway Step Functions and scripting (Python ).
You will architect secure access patterns to cloud-based data systems (e.g. Amazon DynamoDB Amazon RDS Amazon S3 Knowledge Bases for Bedrock) to power AI agent tool use and retrieval-augmented generation (RAG).
You will work with customers to deploy Amazon WorkSpaces Personal Pools and Amazon WorkSpaces Applications as the delivery platform for agentic AI experiences.
You will guide customers through testing evaluation and validation of AI agent performance against defined success criteria before production deployment.
You will create reusable artifacts reference architectures implementation guides sample code prompt libraries data readiness checklists that scale best practices across the SA community and partner ecosystem.
You will provide Voice-of-Customer feedback to the Agentic WorkSpaces Service Team based on real-world customer implementations contributing to product roadmap prioritization.
A day in the life
You pair-program with customer developers to build and test AI agent configurations deployed on WorkSpaces environments. You design prompt strategies and evaluate model performance across different foundation models. You configure MCP servers to expose customer APIs databases and tools in a standardized format for agent consumption. You design A2A workflows where workspace agents hand off to or collaborate with specialized agents across the customers enterprise. You deploy and validate WorkSpaces architectures to ensure the desktop substrate is production-ready. You configure knowledge bases and data connectors for RAG-powered agent responses. You conduct architecture reviews and provide prescriptive guidance for production readiness. You document implementation patterns and contribute to the teams knowledge base. You participate in weekly syncs with service teams to share customer feedback and product insights.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger more collaborative teams. Our continual innovation is fueled by the bold ideas fresh perspectives and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve.
- 7 years of specific technology domain areas (e.g. software development cloud computing systems engineering infrastructure security networking data & analytics) experience
- 3 years of design implementation or consulting in applications and infrastructures experience
- Experience with one of the following programming languages: Python Ruby C# or C
- Hands-on experience with agentic AI patterns multi-agent orchestration tool use function calling chain-of-thought reasoning and autonomous agent workflows.
- Familiarity with interoperability protocols such as MCP (Model Context Protocol) for standardized tool integration and/or A2A (Agent-to-Agent) for multi-agent communication.
- Experience with Amazon Bedrock or equivalent foundation model platforms including model invocation agent creation knowledge base configuration and guardrails.
- Understanding of Virtual Desktop Infrastructure (VDI) and Desktop-as-a-Service (DaaS) technology architecture networking identity image management and operational patterns.
- 5 years of infrastructure architecture database architecture and networking experience
- Experience implementing cloud services including migrations and modernization projects or similar
- Experience working with end user or developer communities
- 5 years of experience and practical knowledge with VDI and DaaS solutions preferably Amazon WorkSpaces AppStream 2.0 Citrix or VMware/Omnissa Horizon.
- Hands-on experience building and deploying MCP servers exposing enterprise tools and APIs via Model Context Protocol for dynamic agent tool discovery and invocation.
- Hands-on experience with retrieval-augmented generation (RAG) vector databases and knowledge base configuration for production AI systems.
- AWS Solutions Architect certification (Associate or Professional) and/or AI Practitioner Certification.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at FL Miami - 153600.00 - 207800.00 USD annually
USA GA Atlanta - 153600.00 - 207800.00 USD annually
USA IL Chicago - 153600.00 - 207800.00 USD annually
USA NY New York - 169000.00 - 228600.00 USD annually
USA WA Seattle - 153600.00 - 207800.00 USD annually
Required Experience:
Senior IC
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