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# Artificial Intelligence Engineer

- **Company:** Booz Allen Hamilton Inc.
- **Location:** San Antonio, TX, United States
- **Experience:** Experienced
- **Salary:** $99,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Graph Database, Python (Programming Language), Machine Learning, Language Modeling, OAuth, JSON Web Token, Enterprise Data Management, LangChain, ReactJS, Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, Generative AI, Containerization, Integration Tests, Information Technology, Deployment Automation, ONNX (Open Neural Network Exchange) Format, AutoGen, Integration Frameworks, Ollama, Virtual Agents, Model Context Protocol, Human in the Loop, Databricks, Web Api, Agent2Agent Protocol
- **Published:** October 22, 2026
- **Apply:** https://www.dice.com/job-detail/740634d3-7bea-48a9-847c-40adc55447a1

## About the Role

* 3+ years of experience developing and maintaining production-grade sof tware systems in Python
 * Experience designing and implementing AI agent architectures using LangChain, LangGraph, AutoGen, MCP, or A2A
 * Experience building RAG solutions with Knowledge Graphs and fine-tuning SLMs using ONNX, GGML, or Ollama
 * Experience integrating LLMs, external APIs, and distributed services into production with optimized inference workflows
 * Experience developing AI evaluation frameworks, integration tests, and production validation using ReAct patterns and human-in-the-loop met hodologies
 * Knowledge of secure HTTP APIs, OAuth2, JWT, API Keys, containerization, and CI / CD pipelines
 * Ability to travel up to 25% of the time
 * TS/SCI clearance
 * Bachelor's degree in Computer Science, Engineering, or Data Science
 * DoD 8140 Level II Certification such as Security+, CySA+, or CISSP Certification

Nice If You Have:

 * Experience supporting DoD clients or other federal mission environments
 * Experience with advanced agentic patterns, including prompt caching, guardrails, agent memory, Model Context Protocol ( MCP ) , and agent deployment strategies
 * Experience developing end-to-end chatbot or agent-to-agent ( A2A ) systems
 * Experience with enterprise data and machine learning platforms such as Databricks or Snowflake
 * Experience building or managing large-scale data processing pipelines
 * Master's degree in a related field

## Description

In this role, you will help evolve traditional LLM-driven solutions into goal-oriented, multi-agent architectures leveraging agent-orchestration frameworks, Retrieval-Augmented Generation ( RAG ) , Knowledge Graphs ( KGs ) , and fine-tuned Small Language Models ( SLMs ) . You will contribute to evaluation and monitoring strategies, refine integration workflows, collaborate with cross-functional engineering teams, and develop scalable AI capabilities that translate cutting-edge concepts into operational, mission-ready solutions.