Principal Applied AI Solutions Architect, Amazon Connect, EMEA Applied AI Solution Architecture team

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.

Are you a customer-obsessed builder with a passion for helping customers achieve their full potential Do you have the technical background customer experience and skills necessary to help accelerate customer adoption of Amazon Connects AI capabilities Do you love building new strategic and data-driven businesses Join the Applied AI Solutions team as an Amazon Connect Specialist Solutions Architect!

The Applied AI Solutions Architecture team is seeking a hands-on customer-obsessed Solutions Architect to accelerate customer adoption of Amazon Connects AI capabilities. Applied AI Solutions is part of the AWS Specialist & Partner (ASP) org which works backwards from our customers most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. We pride ourselves on thinking big delivering exceptional results for our customers and working across AWS as #OneTeam.

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. You will help customers evaluate their data landscape identify gaps establish data pipelines and ensure their knowledge bases CRMs and backend systems are AI-ready before agents go live. You will work at the intersection of contact center operations and applied AI helping customers move from proof-of-concept to pre-production for their Amazon Connect deployments. We stay closely connected to our customers and bring valuable data and insights to our product teams strengthening the product roadmap. Our team is at its best when a customer is thinking big and needs specialized experience to innovate for their business.

Key job responsibilities
Strategic 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 Architecture and forward deploy 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.
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 Architecture and Development: Build serverless integrations using AWS Lambda API Gateway Step Functions and scripting (Python ) 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 to power AI agent tool use and retrieval-augmented generation (RAG).
Agentic IDE Proficiency: Leverage agentic development environments such as Kiro (and similar AI-assisted IDEs) to accelerate development workflows including spec-driven development agent hooks MCP server configuration and AI-assisted code generation.
Pre-Production Validation: Guide customers through testing evaluation and validation of AI agent performance against defined success criteria before production deployment.
Field Enablement: Share learnings delivering technical deep-dives and mentoring other SAs on agentic AI implementation patterns.

A day in the life
Conducting data readiness assessments identifying gaps in knowledge base coverage and recommending data preparation steps before AI agent configuration
Designing prompt strategies and evaluating model performance across different foundation models
Building Lambda functions and API integrations that serve as tools for AI agents
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 customers enterprise
Configuring knowledge bases and data connectors for RAG-powered agent responses
Running evaluation frameworks to measure AI agent accuracy latency and customer satisfaction
Conducting architecture reviews and providing prescriptive guidance for production readiness
Documenting implementation patterns and contributing to the teams knowledge base

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 Connects Unlimited AI features.

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
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Work/Life Balance
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- Bachelors degree in computer science engineering mathematics or equivalent
- 10 years of specific technology domain areas (e.g. software development cloud computing systems engineering infrastructure security networking data & analytics) experience
- Experience developing technology solutions and evangelising end-to-end technology roadmaps that guide IT transformations toward cloud computing
- Experience communicating across technical and non-technical audiences and at C-level including training workshops publications

- Experience with agentic AI patterns including multi-agent orchestration tool use function calling chain-of-thought reasoning and autonomous agent workflows
- Experience with CX/CCaaS adjacent capabilities including Analytics WFM/WFO CRM technologies.
- 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 Connect or other enterprise contact center platforms (Genesys Avaya Cisco NICE Five9 etc.)

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