Amazon Web Services, Inc.
Cloud Computing
SeniorAppliedAISolutionsArchitect
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“Senior Applied AI Solutions Architect at Amazon Web Services, Inc.. Skills: Applied AI, Amazon Connect, Solutions Architecture, Customer data readiness. Accelerate customer adoption of Amazon Connect AI capabilities. Prepare Amazon Connect implementations for production”
What You'll Achieve.
Achieve production-ready outcomes in weeks; Ensure AI agents reliably access information; Ensure AI agents reliably retrieve information; Ensure AI agents reliably act on information; Validate AI agent performance
Industry & Context.
Root cause analysis; Troubleshooting; Data-driven decision making
Up to 25-40% travel
What They're Looking For.
Must Have
5+ years experience, 5+ years experience with AWS, 5+ years experience with Amazon Connect, 5+ years experience with AI/ML, 5+ years experience with contact center AI
Nice to Have
Experience with AWS AI services, Experience with Amazon Bedrock, Experience with MCP servers, Experience with A2A communication patterns, Experience with RAG
What You'll Do.
Accelerate customer adoption of Amazon Connect AI capabilities
Prepare Amazon Connect implementations for production
Guide customers evaluating foundation models
Architect and build tool integrations
Configure MCP servers
Enable A2A communication patterns
Assess customer data assets
Prepare customer data assets
Structure customer data assets
Establish data pipelines
Ensure knowledge bases are AI-ready
Ensure CRMs are AI-ready
Ensure backend systems are AI-ready
Help customers move from proof-of-concept to pre-production
Pair-program with customer teams
Lead technical discovery sessions
Understand business requirements
Understand contact center architecture
Understand AI readiness
Translate findings into implementation plans
Conduct data readiness assessments
Evaluate data quality
Evaluate data accessibility
Evaluate data structure
Evaluate data governance
Recommend remediation strategies
Build data foundation for AI agents
Design and configure agentic AI solutions
Configure AI prompt engineering
Configure model selection
Configure tool integration
Design and deploy MCP servers
Expose customer tools
Expose customer data sources
Enable AI agents to discover tools
Enable AI agents to invoke tools
Architect Agent-to-Agent communication patterns
Allow AI agents to collaborate
Enable multi-agent workflows
Build serverless integrations
Connect AI agents with customer data systems
Architect secure access patterns
Power AI agent tool use
Guide customers through testing
Guide customers through evaluation
Guide customers through validation
Create reusable artifacts
Provide feedback to product teams
Contribute to product roadmap prioritization
How You'll Work.
Team & Collaboration
Customer teams; Customer engineering teams; Service team collaboration; Product teams
Communication Scope
Technical discovery; Implementation plans
Full Job Description
Application deadline: May 3, 2026 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. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges. The Applied AI Solutions Architecture team within AWS is seeking a hands-on, customer-obsessed Solutions Architect to accelerate customer adoption of Amazon Connect's AI capabilities. This role is part of the AI Velocity Team — a service-specific approach that assigns dedicated advisory and hands-on development 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 Amazon Connect implementations for production by focusing on three critical pillars of agentic AI: Model Selection — Guiding customers through evaluating and selecting the right foundation models (via Amazon Bedrock) for their contact center use cases, balancing latency, accuracy, cost, and compliance requirements. Prompt Configuration — Designing, testing, and optimizing AI prompts and system instructions for Amazon Connect AI agents, including self-service agents, answer 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 customers and agents — 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 sy
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