RAG Application Engineer

Retrieval-Augmented Generation (RAG) systems require reliable, well-orchestrated runtime logic to integrate search, models, and metadata into a single coherent experience. As a RAG Application Engineer, you will build the application layer that makes this possible. You will implement the end-to-end query workflow, including embedding generation, hybrid retrieval, reranking, citation assembly, and request-level guardrails, ensuring analysts can access grounded, high-quality responses ’re looking for an engineer who can design and maintain RAG runtime logic in a secure, cloud-based environment.

On our team, you’ll develop API endpoints, manage model integrations, enforce authentication and authorization controls, and implement robust retry, timeout, and error-handling strategies. You’ll containerize services and partner closely with Cloud, Security, Data, and Site Reliability Engineering teammates to ensure the RAG runtime is stable, secure, observable, and ready for mission use.

• Experience building back-end or platform services using programming languages such as Python or Java
• Experience designing or integrating RAG workflows, including embeddings, hybrid retrieval, vector search, and reranking
• Experience implementing API request pipelines, orchestration logic, and service routing for AI model and search calls
• Experience enforcing authentication and authorization within service logic
• Experience developing resilient services with retry, backoff, timeout, and error-handling strategies and collaborating with data, search, cloud, and security engineers to optimize retrieval behavior
• Experience containerizing applications using Docker and deploying to ECS, EKS, or Kubernetes
• Experience building telemetry, including structured logs, metrics, and traces
• Ability to translate RAG requirements into clean, maintainable application logic
• TS/SCI clearance
• HS diploma or GED

• Experience integrating Amazon Bedrock model inference into application workflows
• Experience implementing hybrid retrieval with Open Search, including BM25 and vector search
• Experience developing citation assembly logic, grounding validation, or model guardrails
• Experience designing API gateways, rate limiting, caching, or other high-availability patterns
• Experience working with message queues or asynchronous workflows, including Kafka or Amazon SQS
• Experience contributing to evaluation data pipelines or partnering with evaluation scientists
• Experience using infrastructure-as-code frameworks such as Terraform, Cloud Formation, or AWS CDK
• Ability to collaborate across multiple engineering disciplines
• Possession of excellent communication skills

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.

As part of Booz Allen’s skills first hiring process, candidates must complete the required skills assessment to ensure they meet the Basic Qualifications for this role. Candidates must complete the assessment and meet the minimum proficiency threshold to continue in the hiring process.

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