About the Role
We are seeking an AWS Knowledge Bases Specialist to design, build, and support grounded AI assistants using Amazon Bedrock Knowledge Bases and enterprise content. The ideal candidate will collaborate with business, data, and engineering teams to develop secure, scalable, and measurable AI solutions that deliver accurate, context-aware responses through Retrieval-Augmented Generation (RAG).
Key Responsibilities
- Design, develop, and manage Amazon Bedrock Knowledge Bases for enterprise AI applications.
- Build Retrieval-Augmented Generation (RAG) solutions using enterprise documents and structured knowledge sources.
- Create and optimize embedding pipelines for semantic search and intelligent information retrieval.
- Configure and manage Amazon OpenSearch for indexing and vector search capabilities.
- Design scalable data ingestion workflows using Amazon S3 and AWS-native services.
- Implement secure access controls and governance policies for enterprise knowledge assets.
- Collaborate with AI engineers, cloud architects, data engineers, and business stakeholders to develop intelligent AI assistants.
- Optimize retrieval accuracy, grounding quality, and response relevance.
- Monitor knowledge base performance and continuously improve search effectiveness.
- Maintain technical documentation, deployment standards, and operational best practices.
Required Skills
- Hands-on experience with Amazon Bedrock Knowledge Bases
- Strong understanding of embeddings and semantic search
- Experience with Amazon OpenSearch
- Knowledge of Amazon S3 and enterprise data storage
- Hands-on experience with Retrieval-Augmented Generation (RAG)
- Experience implementing access controls and security best practices
- Strong programming skills in Python
Experience Requirements
- Up to 5 years of overall experience
- Minimum 1–2 years of relevant hands-on experience in Amazon Bedrock, Knowledge Bases, AWS cloud services, Generative AI, or related technologies
