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

About the role

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.

Responsibilities

• Lead technical discovery sessions with customer teams to understand business requirements, existing contact center architecture, and AI readiness.
• Translate findings into actionable implementation plans.
• 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.
• Design and configure agentic AI solutions within Amazon Connect, including AI agent creation, AI prompt engineering, model selection, guardrail configuration, and tool/action integration.
• 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.
• Architect Agent-to-Agent (A2A) 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.
• 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).
• 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).
• Guide customers through testing, evaluation, and validation of AI agent performance against defined success criteria before production deployment.
• 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.
• Provide feedback to Amazon Connect and Amazon Bedrock product teams based on real-world customer implementations, contributing to product roadmap prioritization.

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.
• 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).