AIOps Engineer

Booz Allen Hamilton•St. Louis, MO

1d•$77,600 - $176,000

About The Position

Booz Allen is seeking an AIOps Engineer to develop tools and solutions that use artificial intelligence to improve critical IT operations supporting national security requirements. The role focuses on streamlining IT operations and improving platform productivity by automating operational workflows, building AI agents, and delivering solutions that address client challenges. The engineer will apply knowledge of AIOps, MLOps, ModelOps, and DataOps, and work with cloud, platform, data, and cybersecurity engineers to take technical designs from concept through implementation. The role involves designing, developing, deploying, and maintaining enterprise software, intelligent automation solutions, and operational platforms. It includes implementing monitoring, observability, AIOps, site reliability engineering, and platform operations capabilities, as well as developing Python applications and automation workflows integrated with platform APIs, operational data, audit logs, and cloud services. The position also supports containerized applications and cloud-based logging, monitoring, and telemetry solutions. Applicants must have a TS/SCI clearance with a polygraph and a bachelor's degree. The projected annual compensation range is $77,600 to $176,000. Booz Allen describes benefits that include health, life, disability, financial, and retirement benefits, paid leave, professional development, tuition assistance, work-life programs, dependent care, and recognition awards. The company also describes an identity verification process involving biometrics and AI, and prohibits AI assistance during interviews unless explicitly permitted.

Requirements

At least 5 years of experience designing, developing, deploying, and maintaining enterprise software, intelligent automation solutions, or operational platforms.
At least 3 years of experience implementing monitoring, observability, AIOps, site reliability engineering, or platform operations capabilities, including telemetry, alerting, incident triage, and operational reporting.
Experience designing and deploying AI agents or automated workflows for platform administration, system monitoring, governance, resource optimization, or operational support.
Experience developing applications, services, and automation workflows using Python and integrating them with platform APIs, operational data, audit logs, or cloud services.
Experience deploying and operating containerized applications using orchestration technologies such as Docker, Kubernetes, Helm, or AWS EKS.
Experience integrating cloud-based logging, monitoring, and telemetry solutions to improve platform reliability, performance, scalability, and operational efficiency.
Experience collaborating with cloud, platform, data, and cybersecurity engineers to drive technical designs through implementation and communicate technical progress, demonstrations, risks, and outcomes to stakeholders.
TS/SCI clearance with a polygraph.
Bachelor's degree.

Nice To Haves

Experience developing AI agents, copilots, or agentic workflows with human oversight for incident triage, compliance monitoring, platform administration, or user support.
Experience with Databricks, MLflow, model monitoring, Unity Catalog, system tables, or AI/ML platform operations.
Experience implementing cost and resource optimization capabilities using FinOps practices, usage telemetry, automated recommendations, or resource allocation workflows.
Experience implementing event-driven automation using AWS services such as Lambda, S3 Events, SQS, EventBridge, Step Functions, or Amazon Bedrock.
Experience creating continuous automation across infrastructure, platform, application, security, and operational technology stacks using Git-based CI/CD practices.
Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
AWS, Kubernetes, Databricks, or similar industry certification.

Responsibilities

Design, develop, deploy, and maintain enterprise software, intelligent automation solutions, and operational platforms.
Implement monitoring, observability, AIOps, site reliability engineering, and platform operations capabilities, including telemetry, alerting, incident triage, and operational reporting.
Design and deploy AI agents and automated workflows for platform administration, system monitoring, governance, resource optimization, or operational support.
Develop applications, services, and automation workflows using Python, integrating them with platform APIs, operational data, audit logs, or cloud services.
Deploy and operate containerized applications using orchestration technologies such as Docker, Kubernetes, Helm, or AWS EKS.
Integrate cloud-based logging, monitoring, and telemetry solutions to improve platform reliability, performance, scalability, and operational efficiency.
Collaborate with cloud, platform, data, and cybersecurity engineers to take technical designs from concept through implementation.
Communicate technical progress, demonstrations, risks, and outcomes to stakeholders.
Automate operational workflows and build AI agents to streamline IT operations and improve platform productivity.