Expert Agent Builder – Amazon Bedrock (Amazon Q / QuickSight)

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Expert Agent Builder – Amazon Bedrock (Amazon Q / QuickSight)

Location: Malvern, PA (Local or Nearby Candidates Preferred)

Job Summary

We are seeking an experienced Expert Agent Builder to design, develop, and scale enterprise-grade AI agents using Amazon Bedrock and modern Generative AI frameworks. The ideal candidate will have strong expertise in building autonomous AI agents, implementing Retrieval-Augmented Generation (RAG) architectures, and integrating AI-driven analytics solutions using Amazon Q for Business and Amazon QuickSight.

This role requires hands-on experience with agent orchestration, prompt engineering, LLM integrations, AWS-native AI services, and secure enterprise deployments.

Key Responsibilities

AI Agent Development

• Design, develop, and deploy production-ready AI agents using Amazon Bedrock and foundation models.
• Build autonomous and task-oriented agents capable of planning, reasoning, tool usage, and multi-step execution.
• Implement agentic workflows using frameworks such as LangChain, Semantic Kernel, LlamaIndex, or custom orchestration layers.
• Develop scalable RAG pipelines leveraging enterprise data sources and vector databases.
  
  

Amazon Q for Business

• Configure, customize, and extend Amazon Q for Business for enterprise knowledge discovery and workflow automation.
• Develop custom connectors, personas, permissions, and access control strategies.
• Enable conversational enterprise search and intelligent workflow experiences.
  
  

Analytics & Insights Integration

• Integrate AI agents with Amazon QuickSight to enable conversational analytics, reporting, and business insights.
• Build data-driven AI experiences that support enterprise decision-making.
  
  

Prompt Engineering & LLM Optimization

• Create and optimize prompts, prompt chains, system prompts, and context management strategies.
• Improve LLM output quality, reliability, and response consistency.
• Continuously evaluate and fine-tune prompts based on business use cases and model performance.
  
  

AWS Architecture & Governance

• Design secure, scalable, and enterprise-grade AWS AI architectures.
• Implement AI guardrails, governance, and responsible AI practices.
• Ensure compliance with enterprise security standards and best practices.
  
  

Required Skills & Qualifications

• 7 years of experience in Software Engineering, Cloud Engineering, AI/ML, or related fields.
• Hands-on expertise with Amazon Bedrock, including:
• Foundation model integration
• Bedrock Guardrails
• Bedrock Knowledge Bases
• Model customization
• Strong experience building autonomous AI agents using:
• LangChain
• Semantic Kernel
• LlamaIndex
• Custom orchestration frameworks
• Strong understanding of:
• LLM behavior
• RAG architecture
• Agentic AI workflows
• Multi-agent systems
• Advanced prompt engineering skills including prompt chaining and optimization.
• Strong Python programming and API integration experience.
• Experience with vector databases such as:
• Pinecone
• FAISS
• OpenSearch Vector Engine
• Strong AWS cloud and security expertise.
• Experience deploying AI/GenAI applications in enterprise environments.
  
  

Preferred Qualifications

• Experience with Amazon Q for Business implementations.
• Experience integrating Amazon Bedrock with Amazon QuickSight.
• Familiarity with regulated industry environments.
• Experience working within AI Centers of Excellence (CoE).
• AWS Certifications preferred.
  
  

Technologies & Tools

• Amazon Bedrock
• Amazon Q for Business
• Amazon QuickSight
• LangChain
• Semantic Kernel
• LlamaIndex
• Python
• AWS Services
• Vector Databases (FAISS, Pinecone, OpenSearch)
• REST APIs
• Generative AI / Agentic AI