Senior Applied AI Solutions Architect — Amazon Connect, Applied AI SA - AIVT

Amazon Web Services (AWS); Arlington (VA); On-site; USD 154,000 - 208,000; Full time

Job summary

Amazon Web Services, Inc. is seeking a data‑driven Solutions Architect to accelerate customer adoption of Amazon Connect AI capabilities.

You will be embedded with customers, writing code, building integrations, and pairing with customer engineers to produce production‑ready outcomes in weeks rather than months. You will design agentic AI solutions, configure MCP servers, and enable cross‑team collaboration with engineering, product, and customer success teams.

Qualifications

• 7+ years in software development, cloud computing, or related domains.
• 3+ years in design, implementation, or consulting for applications and infrastructures.
• Familiarity with MCP and A2A interoperability protocols.
• Experience with AI/ML concepts including LLMs, prompt engineering, RAG.

Responsibilities

• Lead technical discovery sessions with customers to understand business requirements and AI readiness.
• Design and configure agentic AI solutions within Amazon Connect, including AI agent creation and prompt engineering.
• Design MCP servers exposing customer tools, data sources, and APIs in a standardized format.
• Architect Agent‑to‑Agent workflows enabling multi‑agent collaboration across the enterprise.
• Build serverless integrations using AWS Lambda, API Gateway, Step Functions, and scripting (Python, Node.js).
• Guide customers through testing and validation of AI agent performance before production deployment.

Skills

7+ years experience

3+ years design/implementation

Interoperability MCP/A2A

AI/ML basics

Tools

AWS Lambda

API Gateway

Step Functions

Python

Node.js

Job description

Description

Application deadline: Aug 25, 2026

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. This role is part of the AI Velocity Team – a service‑specific approach that assigns dedicated advisory and hands‑on development resources directly to customers to achieve production‑ready outcomes in weeks instead of months.

As an Applied AI Solutions Architect, you will be embedded with customers to help them prepare their Amazon Connect implementations for production by focusing on three critical pillars of Agentic AI.

Willingness to travel up to 25-40% for on-site customer engagements.

This is a deeply technical, hands‑on role – you will write code, build integrations, configure agents, and pair‑program with customer engineering teams.

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.

About The Team

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

• 7+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• Familiarity with interoperability protocols such as MCP (Model Context Protocol) for standardized tool integration and/or A2A (Agent‑to‑Agent) for multi‑agent communication
• Demonstrated experience with AI/ML concepts including large language models (LLMs), prompt engineering, retrieval‑augmented generation (RAG), and model evaluation

Preferred Qualifications

• Hands‑on experience with Amazon Bedrock, including model invocation, agent creation, knowledge base configuration, and guardrails
• 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
• 2+ years of contact center experience, or experience with AWS services or other cloud offerings

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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.

The base salary range for this position is listed below. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, San Francisco - 176,600.00 - 239,000.00 USD annually

USA, CO, Denver - 153,600.00 - 207,800.00 USD annually

USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually

USA, IL, Chicago - 153,600.00 - 207,800.00 USD annually

USA, NY, New York - 169,000.00 - 228,600.00 USD annually

USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually

USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually

USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually

Company

Amazon Web Services, Inc.

Job ID: A10435915