Senior Applied AI Solutions Architect — Amazon Connect

Amazon • Herndon, VA

1d

About The Position

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:

Model Selection — Guiding customers through evaluating and selecting the right
foundation models (via Amazon Bedrock) for their contact center use cases,
balancing latency, accuracy, cost, and compliance requirements.

Prompt Configuration — Designing, testing, and optimizing AI prompts and system
instructions for Amazon Connect AI agents, including self-service agents, answer
recommendation agents, and custom orchestrator agents.

Tool Configuration — Architecting and building the tool integrations (APIs,
Lambda functions, data connectors, knowledge bases) that agentic AI systems use
to take actions on behalf of customers and agents — including configuring MCP
(Model Context Protocol) servers for standardized tool discovery and invocation,
and enabling A2A (Agent-to-Agent) communication patterns for multi-agent
orchestration across enterprise systems.

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 + Unlimited AI deployments. This is a deeply technical, hands-on role —
you will write code, build integrations, configure agents, and pair-program with
customer engineering teams.

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

Requirements

• 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
• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• Willingness to travel up to 25-40% for on-site customer engagements
• 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

Nice To Haves

• 2+ years of contact center experience, or experience with AWS services or other cloud offerings
• Experience with CI/CD pipelines build processes
• AWS certification, such as, AWS Solutions Architect, or a similar cloud certification
• Bachelor's degree or above in computer science, machine learning, engineering, or related fields
• 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

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.

Benefits

• 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
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level