AIOps Engineer

Booz Allen Hamilton•Alexandria, VA

13h•$77,600 - $176,000•Onsite

About The Position

Booz Allen is seeking an AIOps Engineer to develop tools and capabilities that improve critical IT operations supporting national security. The role focuses on streamlining IT operations, enhancing platform productivity, automating operational workflows, and building AI agents. The engineer will apply knowledge of AIOps, MLOps, ModelOps, and DataOps to develop and deploy solutions that help address client operational challenges. The position is based in Alexandria, Virginia, with an additional location in St. Louis, Missouri. It is not listed as remote. Applicants must hold a TS/SCI clearance with a polygraph. The projected annual compensation range is $77,600 to $176,000, with salary determined by factors including location, qualifications, experience, and organizational requirements. Booz Allen offers health, life, disability, financial, and retirement benefits, paid leave, professional development, tuition assistance, work-life programs, dependent care, and recognition awards. Eligibility for benefit programs generally applies to full-time and part-time employees working at least 20 hours per week on a regular basis.

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 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

Develop tools and solutions using AIOps, MLOps, ModelOps, and DataOps capabilities to improve critical IT operations.
Streamline IT operations and enhance platform productivity in support of national security.
Automate operational workflows and build AI agents.
Design, develop, deploy, and maintain enterprise software, intelligent automation solutions, or operational platforms.
Implement monitoring, observability, AIOps, site reliability engineering, or platform operations capabilities, including telemetry, alerting, incident triage, and operational reporting.
Design and deploy AI agents or 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 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.