RAG Data Engineer The Opportunity:
As a RAG Data Engineer, you will build and operate the data ingestion and search infrastructure that powers mission-critical Retrieval-Augmented Generation (RAG) capabilities. You will design, implement, and maintain pipelines that transform structured and unstructured information into retrieval-ready assets, enabling AI-powered applications to deliver accurate, grounded, and relevant responses.
You will own the ingestion, embedding, and indexing workflows that connect enterprise data sources with Amazon Bedrock and OpenSearch. Your responsibilities will include document normalization, chunking strategies, embedding generation, metadata enrichment, lineage tracking, and reliable upsert or delete operations. You will also design and optimize OpenSearch indexes, mappings, shard configurations, lifecycle policies, and query performance.
Working alongside cloud architects, security engineers, application developers, and AI/ML specialists, you will help establish a scalable, secure, and resilient data retrieval foundation. Your work will directly support the development and deployment of enterprise RAG applications.
Work with us to use data for good.
Join us. The world can’t wait.
You Have:
Experience developing and maintaining ETL or data ingestion pipelines for structured and unstructured data
Experience implementing document normalization, parsing, chunking, and content preparation workflows, and generating embeddings and integrating embedding workflows into data processing pipelines
Experience designing and maintaining OpenSearch or Elasticsearch indexes, schemas, mappings, and aliases, and optimizing search performance, including query tuning, indexing efficiency, and shard management
Experience implementing idempotent ingestion processes, including upsert, delete, replay, and failure recovery
Experience with metadata modeling, enrichment, lineage, and version tracking
Experience with Python or programming languages for data engineering and automation
Experience with containerized applications or deployment environments such as Docker, ECS, EKS, or Kubernetes
Ability to collaborate with engineering, security, cloud, and application development teams
TS/SCI clearance
HS diploma or GED
Nice If You Have:
Experience integrating Amazon Bedrock embeddings into RAG ingestion pipelines
Experience tuning hybrid retrieval systems combining BM25 keyword search and vector similarity search
Experience implementing OpenSearch lifecycle policies, snapshots, restoration, and index migration strategies
Experience with distributed or asynchronous data processing using Spark, Ray, Dask, Kafka, or Amazon SQS
Experience optimizing document chunking, embeddings, and indexing strategies using retrieval evaluation results
Experience handling multi-source data ingestion and cross-source normalization
Experience designing scalable, secure data infrastructure using AWS services
Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or AWS CDK
Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by…