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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Booz Allen Hamilton Inc. - **Location:** Washington, United States - **Experience:** Experienced - **Salary:** $99,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Confluence, Cloud Computing Security, Cloud Engineering, Encodings, Information Leak Prevention, Software Debugging, Identity and Access Management, PostgreSQL, Machine Learning, Enterprise Messaging Systems, Node.Js, Performance Tuning, RabbitMQ, Redis, Regression Testing, Search Technologies, Microsoft SharePoint, Systems Integration, Management of Software Versions, Web Services, Enterprise Data Management, Datadog, Data Logging, Flask (Web Framework), Large Language Models, Snowflake, Multi-Agent Systems, Parallel Computation, Indexer, Fastapi, Event Driven Architecture, AI Platforms, Low Latency, Apache Kafka, Functional Programming, Cloudwatch, Amazon Simple Queue Service (SQS), Databricks - **Published:** August 15, 2026 - **Apply:** https://www.dice.com/job-detail/dfdcdb60-cf92-4e5b-b5a3-aad874c77dc5 ## About the Role * 3+ years of experience building production systems, including AI / ML applications * Experience building LLM systems using RAG frameworks such as LangChain and LlamaIndex, or custom pipelines and vector stores with Pinecone, Weaviate, FAISS, or OpenSearch Vector Search * Experience designing embedding pipelines, including document ingestion, chunking strategies, indexing, met adata filtering, retrieval optimization, and hybrid search, and designing APIs and services using FastAPI, Flask, or Node.js * Experience with cloud-native architectures, including AWS services such as Bedrock, SageMaker, EKS or ECS, S3, IAM, Lambda, CloudWatch, and Secrets Manager, and agent frameworks and orchestration patterns such as LangGraph, tool calling, and function calling APIs * Experience implementing observability, including logging and tracing with OpenTele met ry, Datadog, or CloudWatch, and met rics pipelines tracking latency, throughput, token usage, cache hit rate, and error rates * Experience optimizing performance using caching layers such as Redis, parallelization or async workflows, and chunking and retrieval tuning, and designing automated evaluation pipelines using benchmark datasets, LLM-as-a-judge techniques, regression testing, and human evaluation workflows * Experience supporting production AI services, including deployment, monitoring, incident response, debugging, and performance tuning, and managing prompt templates, prompt versioning, model configurations, and structured outputs across development and production environments * Knowledge of AI security concepts, including prompt injection, jailbreak resistance, data leakage prevention, guardrails, secure prompt design, and responsible AI practices * Ability to obtain a TS/SCI clearance * Bachelor's degree Nice If You Have: * Experience supporting DoD clients or other federal mission environments * Experience with high-performance inference systems such as vLLM, Ray Serve, or Triton Inference Server * Experience with semantic caching and embedding reuse strategies * Experience with guardrail frameworks such as Rebuff, Guardrails.ai, or custom filtering systems * Experience integrating AI applications with enterprise data platforms and knowledge repositories such as Databricks, Snowflake, OpenSearch, PostgreSQL, SharePoint, Confluence, or S3-based document stores * Experience deploying AI workloads into AWS GovCloud, IL4 or IL5 environments, or other secure cloud environments * Experience with event-driven architectures and messaging technologies such as Amazon SQS, Kafka, RabbitMQ, or Amazon EventBridge * Experience with Model Context Protocol ( MCP ) or modern AI agent interoperability standards ## Related Videos - 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