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

Job in Mountain View, Santa Clara County, California, 94039, USA
Listing for: Amazon Web Services (AWS)
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Description

Apply. This position is part of the AWS Specialist and Partner Organization (ASP) and focuses on accelerating customer adoption of Amazon Connect's AI capabilities within the Applied AI Solutions Architecture team. In this hands‑on, customer‑obsessed role you will help customers prepare their Amazon Connect implementations for production by guiding them through model selection, prompt configuration, tool configuration, and ensuring customer data readiness for Agentic AI.

Travel of 25–40% for on‑site customer engagements is expected.

Key Job Responsibilities
  • Customer Engagement:
    Lead technical discovery sessions with customer teams to understand business requirements, existing contact center architecture, and AI readiness, translating 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 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 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 Dynamo

    DB, Amazon RDS, Amazon S3, Amazon Open Search, 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.
Basic Qualifications
  • 7+ years of specific technology domain experience (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
  • 3+ years of design, implementation, or consulting experience in applications and infrastructures.
  • Familiari…
Position Requirements
10+ Years work experience
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