Sr. Applied AI Solutions Architect - Public Sector, Amazon Connect

About the role

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.

Key job responsibilities

• Customer Engagement: Lead technical discovery sessions with customer teams to understand business requirements, existing contact center architecture, and AI readiness. Translate findings into actionable implementation plans.
• Customer Data Readiness: Conduct data readiness assessments to evaluate the quality, accessibility, structure, and governance of customer data assets (CRMs, knowledge bases, ticketing systems, order management, etc.). Identify data gaps, recommend remediation strategies, and help customers build the data foundation required for effective AI agent tool use and RAG-powered responses.
• Agentic AI Implementation: Design and configure agentic AI solutions within Amazon Connect, including AI agent creation, AI prompt engineering, model selection, guardrail configuration, and tool/action integration.
• MCP Server Configuration: Design and deploy Model Context Protocol (MCP) servers that expose customer tools, data sources, and APIs in a standardized format — enabling AI agents to dynamically discover and invoke capabilities across the customer's technology stack.
• A2A (Agent-to-Agent) Integration: Architect Agent-to-Agent communication patterns that allow Amazon Connect AI agents to collaborate with specialized agents across the enterprise (e.g., billing agents, order management agents, IT support agents), enabling multi-agent workflows that span organizational boundaries.
• Integration Development: Build serverless integrations using AWS Lambda, API Gateway, Step Functions, and scripting (Python, Node.js) to connect Amazon Connect AI agents with customer data systems (CRMs, ERPs, databases, knowledge bases).
• Cloud Data Access: Architect secure access patterns to cloud-based data systems (Amazon DynamoDB, Amazon RDS, Amazon S3, Amazon OpenSearch, Amazon Kendra/Knowledge Bases for Bedrock) to power AI agent tool use and retrieval-augmented generation (RAG).
• Pre-Production Validation: Guide customers through testing, evaluation, and validation of AI agent performance against defined success criteria before production deployment.
• Knowledge Sharing: Create reusable artifacts (reference architectures, implementation guides, sample code, prompt libraries, data readiness checklists) that scale best practices across the Connect SA community and partner ecosystem.
• Service Team Collaboration: Provide feedback to Amazon Connect and Amazon Bedrock product teams based on real-world customer implementations, contributing to product roadmap prioritization.

A day in the life

• Pair-programming with customer developers to build and test AI agent configurations
• Designing prompt strategies and evaluating model performance across different foundation models
• Configuring MCP servers to expose customer APIs, databases, and tools in a standardized format for agent consumption
• Designing A2A workflows where Amazon Connect agents hand off to or collaborate with specialized agents across the customer's enterprise
• Configuring knowledge bases and data connectors for RAG-powered agent responses
• Conducting architecture reviews and providing prescriptive guidance for production readiness
• Documenting implementation patterns and contributing to the team's knowledge base
• Participating in weekly syncs with Connect service teams to share customer feedback and product insights

Basic Qualifications

• 6+ years of design, implementation, or consulting in applications and infrastructures experience
• Experience with Amazon Connect or other enterprise contact center platforms (Genesys, Avaya, Cisco, NICE, Five9, etc.)
• Hands-on experience with Amazon Bedrock, including model invocation, agent creation, knowledge base configuration, and guardrails

Preferred Qualifications

• 5+ years of infrastructure architecture, database architecture and networking experience
• Experience with agentic AI patterns — multi-agent orchestration, tool use, function calling, chain-of-thought reasoning, and autonomous agent workflows
• Hands-on experience building and deploying MCP servers — exposing enterprise tools and APIs via Model Context Protocol for dynamic agent tool discovery and invocation
• Experience designing A2A (Agent-to-Agent) architectures — enabling specialized agents to collaborate across domains (e.g., billing, logistics, IT) through standardized agent communication protocols
• Proficiency with agentic IDEs such as Kiro, Cursor, or similar AI-assisted development environments, including experience with agent hooks, agent steering, MCP server configuration, and spec-driven development
• AWS certifications (Solutions Architect Professional, AI Practitioner, Machine Learning Specialty)

About the team

The Applied AI Solutions Architecture team is part of the AWS Specialist and Partner Organization (ASP). We are the technical bridge between Amazon Connect customers and the service teams building the next generation of AI-powered contact center capabilities. Our team operates at the forefront of agentic AI adoption, helping customers become production-ready with Amazon Connect's Unlimited AI features.