Sr. Applied AI Solutions Architect, Amazon Connect

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 Connect's 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 Connect's AI capabilities. Applied AI Solutions is part of the AWS Specialist & Partner (ASP) org, which works backwards from our customer’s 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
* 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.
* 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 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 customer's 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 team's knowledge base

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s 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
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll 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, there’s nothing we can’t achieve.

Basic Qualifications

- Experience in design, implementation, or consulting in applications and infrastructures
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- 5+ years of experience building integrations across AI, Agentic AI, CRM, and contact center solutions or experience with communications protocols and APIs such as WebRTC and SIP or similar CCaaS technology. Experience with complex Contact Center as a Service (CCaaS) implementations
- 5+ years of experience building integrations across WFM, CRM, and contact center solutions or experience with communications protocols and APIs such as WebRTC and SIP or similar CCaaS technology
- Experience with complex Contact Center as a Service (CCaaS) implementations

Preferred Qualifications

- Experience in infrastructure architecture, database architecture and networking
- Presentation skills with a high degree of comfort speaking with executives, IT Management, and developers.
- History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises.
- AWS Solution Architecture certification or relevant cloud expertise

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