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

Amazon is hiring a Principal Applied AI Solutions Architect, Amazon Connect, EMEA Applied AI Solution Architecture team in London, United Kingdom. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this solutions architect role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include prompt engineering, RAG and AI agents.
Level classifies it as a lead role.
Level lists 20,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

prompt-engineeringragai-agents

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 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
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, 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
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.

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, 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
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

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

- Bachelor's 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

Preferred qualifications

- 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.)

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Principal Applied AI Solutions Architect, Amazon Connect, EMEA Applied AI Solution Architecture team at Amazon rates 72 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal Applied AI Solutions Architect, Amazon Connect, EMEA Applied AI Solution Architecture team is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in GB, London.
The job was posted on November 3, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agents

Also common in solutions architect jobs at this level

Generative AI Azure LLM Google Cloud Machine learning SQL

Pay

Typical solutions architect job: $169k

This posting doesn't list pay. Use the typical solutions architect figure when pay comes up. See solutions architect jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, and AI agents. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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