Conversational AI Expert - Amazon Bedrock AgentCore and Amazon Connect

Location: Fully Remote
Project: Enterprise Conversational AI Platform Migration to AWS

Project Overview

We are looking for an experienced Conversational AI Expert to support the migration of an existing contact center environment from Genesys and Cognigy AI to Amazon Connect and Amazon Bedrock AgentCore.

The project focuses on building a scalable, enterprise-grade AI platform on AWS, with particular emphasis on Retrieval-Augmented Generation (RAG), enterprise knowledge integration, and multi-agent orchestration.

A key part of the solution is developing a comprehensive RAG-based knowledge layer that brings together large volumes of enterprise information, including documentation, repositories, internal services, and other knowledge sources. This knowledge must be made accessible to AI agents through appropriate retrieval mechanisms, APIs, gateways, and cloud-based integrations.

The role involves coordinating AI agents and sub-agents across AWS services and integration layers, ensuring reliable access to enterprise knowledge and backend systems. While the platform supports voice and chat channels, the primary focus of this position is on the underlying AI architecture, knowledge retrieval, and agent integration rather than voice technology or telephony implementation.

Key Responsibilities

• Design, implement, and optimize enterprise RAG solutions that enable AI agents to retrieve and use information from large, diverse knowledge sources.
• Integrate enterprise documentation, code repositories, internal services, and other data sources into AI-powered knowledge and retrieval pipelines.
• Configure and orchestrate AI agents and sub-agents using Amazon Bedrock AgentCore and Amazon Connect.
• Design and implement integrations between Amazon Connect AI agents and Amazon Bedrock AgentCore agents and runtime through the Bedrock AgentCore Gateway.
• Coordinate end-to-end interactions between AI agents, retrieval components, AWS services, gateways, APIs, and backend systems.
• Collaborate with the dedicated Bedrock AgentCore development team responsible for agent logic, aligning interfaces, input/output schemas, and error-handling strategies.
• Apply best practices for retrieval quality, prompt engineering, context management, agent guardrails, and reliable access to enterprise knowledge.
• Test, evaluate, and continuously improve the quality, relevance, and reliability of AI-generated responses and agent workflows.
• Document solution patterns, integration guidelines, and architectural decisions, and transfer knowledge to the client and project team.

Required Qualifications

• Several years of hands-on experience building or integrating conversational AI, LLM-based applications, or enterprise AI assistants.
• Practical experience with RAG architectures, including knowledge ingestion, document processing, retrieval pipelines, and grounding LLM responses in enterprise information.
• Experience integrating AI agents with multiple data sources, APIs, repositories, and enterprise backend systems.
• Experience with multi-agent systems, agent orchestration, or integrating LLM-powered components across distributed services.
• Experience with AWS Bedrock in enterprise integration scenarios, ideally including Amazon Bedrock AgentCore and the AgentCore Gateway, or comparable API and gateway technologies.
• Good understanding of AWS services for AI, serverless computing, and integration, such as AWS Lambda, API Gateway, EventBridge, and CloudWatch.
• Ability to work effectively across complex enterprise environments involving multiple teams, services, APIs, and integration layers.
• English proficiency at B1 level or higher, with the ability to communicate effectively in international project teams.

Preferred Qualifications

• Hands-on experience with Amazon Bedrock AgentCore, including agent runtime, gateway integrations, tool access, and orchestration patterns.
• Experience with Amazon Connect AI capabilities and integrations, including contact flows and connecting conversational interfaces to external AI services.
• Familiarity with LangChain and/or LangGraph for implementing RAG pipelines and orchestrating complex LLM or multi-agent workflows.
• Experience designing enterprise knowledge architectures that combine multiple repositories, document sources, internal services, and APIs.
• Experience with monitoring, evaluating, and improving RAG and agent-based systems in production environments.
• Experience with enterprise contact center migrations, particularly from Genesys and/or Cognigy AI to Amazon Connect.
• Fluent business English, including participation in technical workshops and coordination with international stakeholders.

Engagement Details

• Work arrangement: Fully remote
• Primary focus: Enterprise RAG, knowledge integration, multi-agent orchestration, and AWS-based AI integrations
• Technology stack: Amazon Bedrock AgentCore, Amazon Connect, AWS Lambda, API Gateway, EventBridge, CloudWatch, and related AWS services