Job Title: Agent Builder Expert (AI Agents / Amazon Bedrock)
Location: Malvern, PA
Duration: 12+ Months
Experience Required: 8–10+ Years
Important Submission Requirement
The below questions must be answered and included on the candidate’s resume/submission:
- How does agentic AI differ from traditional AI?
- What are the main components of an AI Agent?
- What is the control loop in an AI agent?
- What is planning in Agentic AI?
- How do agents avoid conflicts?
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.
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
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
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
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
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
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
AWS AI Services
Strong experience with:
- Amazon Q for Business
- Amazon QuickSight
- AWS cloud architecture
- Secure enterprise AI deployment
AI Engineering Expertise
Strong understanding of:
- Agentic AI frameworks
- Planning architectures
- Tool-calling agents
- Memory architectures
- Multi-agent orchestration
- RAG architectures
- Prompt engineering / orchestration
Architecture Skills
Experience designing:
- Scalable AWS architectures
- Secure AI systems
- Enterprise governance models
- AI guardrail implementations
Preferred Skills
- Analytics-driven conversational AI use cases
- Enterprise AI governance programs
- Multi-agent enterprise workflow systems
- Production AI observability and monitoring
Soft Skills
- Strong architectural thinking
- Excellent communication skills
- Stakeholder collaboration experience
- Strong problem-solving mindset
Key Skills
- Amazon Bedrock
- AI Agents
- Agentic AI
- Amazon Q for Business
- Amazon QuickSight
- RAG
- Foundation Models
- AWS AI Architecture
- Enterprise AI Governance
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