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# AI Engineer

- **Company:** Booz Allen Hamilton Inc.
- **Location:** Washington, DC, United States
- **Experience:** Experienced
- **Salary:** $99,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Identity and Access Management, Machine Learning, Node.Js, Cloud Services, Azure Machine Learning, Enterprise Data Management, Datadog, Cloud Platform System, Flask (Web Framework), Large Language Models, Snowflake, Multi-Agent Systems, Caching, Generative AI, Fastapi, SC Clearance, Deployment Automation, Machine Learning Operations, Api Design, Cloudwatch, Data Pipelines, Databricks
- **Published:** July 23, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9049116/ai-engineer

## About the Role

* 3+ years of experience building production systems and applications, including AI/ML applications
 * 2+ years of experience developing Generative AI applications using LLMs, RAG frameworks, and vector stores
 * Experience designing and building APIs and services with FastAPI, Flask, or Node.js
 * Experience working in cloud-native environments like AWS and Azure and developing scalable solutions with cloud services like Bedrock/AI Foundry, SageMaker/AI Studio, EKS/ECS, S3, IAM, CloudWatch
 * Experience with agent orchestration frameworks, such as LangGraph and Strands, and tool or function calling patterns
 * Experience implementing observability such as OpenTelemetry, Datadog, or CloudWatch and performance metrics pipelines with dashboards
 * Experience using AI-assisted coding tools such as Copilot, Codex, and Claude Code for complex development tasks
 * Experience deploying models, agents, or applications via CI/CD
 * Ability to obtain a Secret clearance
 * Bachelor's degree in CS, Engineering, or STEM field

 * Experience supporting DoW clients or other federal mission environments
 * Experience with advanced agentic patterns including prompt caching, guardrails, agentic memory, Model Context Protocol (MCP), and agentic deployment strategies
 * Experience with end-to-end chatbot or agent to agent (A2A) development
 * Experience with enterprise data and ML platforms such as Databricks or Snowflake
 * Experience in creating and managing large data processing pipelines
 * Master's degree

## Description

You'll own production AI/ML solutions end to end by building and deploying applications like multi-agent systems in cloud environments. You'll ensure systems are observable and performant, implementing tracing, metrics, and optimizing latency, caching, and retrieval, while designing and evaluating RAG pipelines, applying traditional ML where appropriate, and using AI-assisted coding tools to accelerate delivery.


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