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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Nat Booz Allen - **Location:** 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, 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, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Snowflake, Parallel Computation, Indexer, Fastapi, Event Driven Architecture, AI Platforms, Low Latency, Apache Kafka, Functional Programming, Cloudwatch, Amazon Simple Queue Service (SQS), Databricks - **Published:** September 30, 2026 - **Apply:** https://www.thejobnetwork.com/job/60444af7-bdc4-4b9f-8fbc-457d4e6c1230/ai-engineer ## About the Role * 3+ years of experience building production systems, including AI / ML applications \n * 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 \n * 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 \n * 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 \n * 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 \n * 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 \n * 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, * Experience with high-performance inference systems such as vLLM, Ray Serve, or Triton Inference Server \n * Experience with semantic caching and embedding reuse strategies \n * Experience with guardrail frameworks such as Rebuff, Guardrails.ai, or custom filtering systems \n * Experience integrating AI applications with enterprise data platforms and knowledge repositories such as Databricks, Snowflake, OpenSearch, PostgreSQL, SharePoint, Confluence, or S3-based document stores \n * Experience deploying AI workloads into AWS GovCloud, IL4 or IL5 environments, or other secure cloud environments \n * Experience with event-driven architectures and messaging technologies such as Amazon SQS, Kafka, RabbitMQ, or Amazon EventBridge \n * Experience with Model Context Protocol ( MCP ) or modern AI agent interoperability standards \n ## Related Videos - [The Memory Leak That Ate Our Cluster: A Postmortem](https://www.wearedevelopers.com/videos/2057-the-memory-leak-that-ate-our-cluster-a-postmortem) - [One AI API to Power Them All](https://www.wearedevelopers.com/videos/1601-one-ai-api-to-power-them-all) - [Stop using Node.js like in 2020! What changed and what you can do today with Node.js](https://www.wearedevelopers.com/videos/100011-stop-using-node-js-like-in-2020-what-changed-and-what-you-can-do-today-with-node-js) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Accelerating Authentication Architecture: Taking Passwordless to the Next Level](https://www.wearedevelopers.com/videos/733-accelerating-authentication-architecture-taking-passwordless-to-the-next-level) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Got AI ideas but no money? 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