Operational Technology AI Engineer

Booz Allen Hamilton•Chantilly, VA

6d•$86,800 - $198,000•Remote

About The Position

As a cyber warfare engineer, you know how critical it is to stay ahead of evolving threats by identifying and exploiting vulnerabilities before adversaries can. At Booz Allen, you'll bring that expertise to a mission-focused team where you'll design, develop, and prototype Artificial Intelligence and Machine Learning capabilities specifically for Operational Technology (OT), Industrial Control Systems (ICS), and cyber-physical environments. Work at the intersection of AI, cybersecurity, and operational systems to develop new capabilities that improve OT asset visibility, threat detection, vulnerability analysis, anomaly detection, incident response, and operator decision-making. Analyze OT data sources, including network telemetry, asset inventories, logs, sensor data, process data, threat intelligence, and security alerts to identify opportunities for AI-enabled automation and analytics. Develop and evaluate machine learning models, AI agents, retrieval-augmented generation capabilities, and other AI-enabled tools designed around the unique safety, availability, latency, and mission requirements of OT environments. Partner with OT engineers, cybersecurity specialists, data scientists, and mission stakeholders to move concepts from research and prototypes into deployable capabilities. Evaluate emerging AI technologies and determine how they can be securely applied within on-premises, air-gapped, disconnected, intermittent, and bandwidth-limited environments. This is your opportunity to help advance national security through cutting-edge cyber capabilities. Join us. The world can't wait.

Requirements

3+ years of experience in AI and ML engineering, software engineering, data science, or cybersecurity engineering
Experience developing applications using Python
Experience with machine learning, Large Language Models, AI agents, or generative AI technologies
Experience integrating and analyzing data from multiple structured and unstructured sources
Knowledge of cybersecurity concepts, network security, and threat detection
Ability to develop prototypes and translate technical concepts into operational capabilities
Ability to obtain a Secret clearance
Bachelor's degree in Computer Science, Engineering, Cybersecurity, Data Science, or Artificial Intelligence

Nice To Haves

Experience with Operational Technology, Industrial Control Systems, SCADA, cyber-physical systems, or embedded systems
Experience analyzing OT network traffic, industrial protocols, telemetry, sensor data, or process data
Experience developing AI-enabled cybersecurity capabilities such as anomaly detection, threat hunting, vulnerability prioritization, or automated response
Experience with Retrieval-Augmented Generation (RAG), agentic AI, vector databases, knowledge graphs, or AI orchestration frameworks
Experience deploying AI capabilities to edge, on-premises, air-gapped, or resource-constrained environments
Experience with cloud and container technologies, including Kubernetes and Docker
Knowledge of Purdue Model architectures and industrial protocols such as Modbus, DNP3, OPC UA, BACnet, or EtherNet/IP
Knowledge of AI security, model security, and secure AI development
Top Secret clearance

Responsibilities

Design, develop, and prototype Artificial Intelligence and Machine Learning capabilities for Operational Technology (OT), Industrial Control Systems (ICS), and cyber-physical environments.
Improve OT asset visibility, threat detection, vulnerability analysis, anomaly detection, incident response, and operator decision-making.
Analyze OT data sources (network telemetry, asset inventories, logs, sensor data, process data, threat intelligence, security alerts) to identify opportunities for AI-enabled automation and analytics.
Develop and evaluate machine learning models, AI agents, retrieval-augmented generation capabilities, and other AI-enabled tools for OT environments.
Partner with OT engineers, cybersecurity specialists, data scientists, and mission stakeholders to move concepts from research and prototypes into deployable capabilities.
Evaluate emerging AI technologies and determine how they can be securely applied in various environments (on-premises, air-gapped, disconnected, intermittent, bandwidth-limited).