Senior Applied AI Solutions Architect – Amazon Connect, Applied AI

Senior Applied AI Solutions Architect – Amazon Connect, Applied AI

Job :  | Amazon Web Services, Inc.

This position sits within the AWS Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their technology domains and provide the business and technical expertise that helps our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together, they give our customers the expertise and scale they need to build innovative solutions for their most complex challenges.

Customer experience is being reinvented by applied AI, and Amazon Connect sits at the center of that shift. Our team turns the newest Amazon Connect AI capabilities into working systems and hands‑on experiences that customers, sales teams, and partners can actually use. What we build shortens the path from "is this possible?" to "here’s how it works," accelerates adoption of applied AI on Amazon Connect, and feeds real‑world signal back into the product roadmap.

The reference architectures, demos, and internal assets you create are often the first thing a customer sees, and the fastest way a global sales team can show the art of the possible.

The Applied AI Solutions Architecture team is hiring a hands‑on Solutions Architect to design and deliver AI‑first solutions on Amazon Connect. The role has two halves: you build working systems, reference architectures, and internal assets that advance org‑level initiatives, and you build Live demos that let sales teams, customers, and partners use production‑quality Amazon Connect AI agents.

You work across the full stack, from the user‑facing experience down to the integrations and data behind it, anchored on Amazon Connect. The work covers five areas:

• Prompt configuration:
  Design, test, and tune prompts and system instructions for Amazon Connect AI agents, including self‑service agents, answer recommendation agents, and custom orchestrator agents. Evaluate LLM behavior and tune for reliable performance.
• Agent memory and context:
  Build short‑term, long‑term, and session memory, manage context windows, and structure state so agents stay coherent and personalized across multi‑turn and multi‑agent interactions.
• Tool configuration:
  Build the integrations agents use to take action (APIs, Lambda functions, data connectors, knowledge bases), configure MCP (Model Context Protocol) servers for standardized tool discovery and invocation, and enable A2A (Agent‑to‑Agent) patterns for multi‑agent orchestration.
• Data readiness:
  Assemble and structure realistic datasets and knowledge bases (sample CRMs, ticketing systems, order management) so agents retrieve and act on the right information.
• Well‑Architected:
  Apply the AWS Well‑Architected Framework across operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability.

• Org initiatives:
  Deliver AI‑first solutions for org‑level initiatives, including working systems, reusable reference patterns, and internal assets on Amazon Connect that help the broader organization adopt applied AI.
• Live demos:
  Design, build, and maintain Live demo environments showcasing Amazon Connect AI agents. Turn emerging use cases and new product capabilities into hands‑on experiences.
• Full‑stack development:
  Build front‑end experiences and back‑end services, write REST APIs and web services, and integrate agentic and generative AI into working applications.
• Agent development:
  Configure Amazon Connect AI agents end to end, covering agent creation, prompt engineering, guardrails, LLM evaluation and tuning, and memory and context management across turns and sessions.
• Tools and multi‑agent…