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 visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Identity Statement

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.
• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role.
• Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.