Job Title: Agent Builder Expert (AI Agents / Amazon Bedrock)

Location: Malvern, PA
Duration: 12 Months
Experience Required: 8–10 Years

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Important Submission Requirement

The below questions must be answered and included on the candidate’s resume/submission:

1. How does agentic AI differ from traditional AI?
2. What are the main components of an AI Agent?
3. What is the control loop in an AI agent?
4. What is planning in Agentic AI?
5. How do agents avoid conflicts?

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Job Summary

We are seeking an Expert Agent Builder to design, develop, and deploy production-grade AI agents using Amazon Bedrock, Amazon Q for Business, and AWS-native AI services. The ideal candidate will have strong expertise in agentic AI architectures, RAG pipelines, enterprise AI governance, tool-using agents, and analytics integrations.

This role focuses on building secure, scalable, enterprise-grade conversational and task-oriented AI agents that deliver measurable business value.

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Key Responsibilities

AI Agent Design & Development

• Design, build, and deploy production-ready AI agents using:
  • Amazon Bedrock
  • Foundation Models / LLMs
  • AWS-native AI services
• Implement advanced agentic workflows including:
  • Planning
  • Tool usage
  • Memory
  • Multi-step reasoning
  • Decision orchestration
  • Task execution workflows
• Build secure enterprise-grade conversational and task-oriented agents

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RAG & Knowledge Systems

• Design and implement Retrieval-Augmented Generation (RAG) pipelines leveraging:
  • Enterprise knowledge repositories
  • Internal structured/unstructured data
  • Search and vector retrieval architectures
• Build enterprise knowledge access workflows for AI agents

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Amazon Q for Business

• Configure, customize, and extend Amazon Q for Business
• Implement:
  • Enterprise knowledge discovery workflows
  • Conversational business assistants
  • Role/persona-driven AI experiences
• Configure:
  • Connectors
  • Access controls
  • User permissions
  • Enterprise search integrations

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Analytics & Conversational Insights

• Integrate AI agents with Amazon QuickSight for:
  • Conversational analytics
  • Data-driven business insights
  • Natural language analytical interactions
• Build analytics-enabled intelligent assistants

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Architecture & Governance

• Design secure, scalable AWS AI architectures
• Implement:
  • AI guardrails
  • Governance frameworks
  • Security controls
  • Responsible AI design practices
• Ensure enterprise scalability, observability, reliability, and compliance

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Required Skills & Qualifications

Mandatory Skills

Strong hands-on expertise in:

• Amazon Bedrock (mandatory)
• AI Agent development / Agentic AI architectures (mandatory)
• Foundation Models / LLM implementations
• Enterprise conversational AI development

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AWS AI Services

Strong experience with:

• Amazon Q for Business
• Amazon QuickSight
• AWS cloud architecture
• Secure enterprise AI deployment

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AI Engineering Expertise

Strong understanding of:

• Agentic AI frameworks
• Planning architectures
• Tool-calling agents
• Memory architectures
• Multi-agent orchestration
• RAG architectures
• Prompt engineering / orchestration

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Architecture Skills

Experience designing:

• Scalable AWS architectures
• Secure AI systems
• Enterprise governance models
• AI guardrail implementations

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Preferred Skills

• Analytics-driven conversational AI use cases
• Enterprise AI governance programs
• Multi-agent enterprise workflow systems
• Production AI observability and monitoring

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Soft Skills

• Strong architectural thinking
• Excellent communication skills
• Stakeholder collaboration experience
• Strong problem-solving mindset

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Key Skills

• Amazon Bedrock
• AI Agents
• Agentic AI
• Amazon Q for Business
• Amazon QuickSight
• RAG
• Foundation Models
• AWS AI Architecture
• Enterprise AI Governance