below marketmost similar roles pay hereabove market
This role pays more than
71%
of similar roles. Most pay
$151,000–$213,200
— the blue band above.
At the midpoint, this role pays about
$204k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
1660 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 908 roles with salary data.
The Platform and Reliability Engineer, Senior Manager leads the team responsible for building and operating the secure, reliable foundation for enterprise agentic AI. This role involves providing cloud infrastructure, shared runtimes, model access, deployment pipelines, and observability services. You will automate environments and security controls, monitor latency, throughput, and token consumption, and lead shared-platform incident response. Key responsibilities include validating operational readiness and maintaining deployment standards for AI engineering and data engineering teams. Required technical skills include Infrastructure-as-Code, containers, orchestration, CI/CD pipelines, and tools like Terraform or CloudFormation. You must apply site reliability engineering practices, LLMOps, and distributed systems troubleshooting using Python or Bash. Experience with AWS, Databricks, networking, identity, and secrets management is essential for managing these complex AI workloads.
Build and operate cloud infrastructure, shared runtimes, and deployment pipelines for enterprise agentic AI.
Automate environments and security controls using Infrastructure-as-Code and CI/CD pipelines.
Monitor system availability, latency, throughput, token consumption, and operational costs.
Lead shared-platform incident response, recovery efforts, and disaster recovery planning.
Implement centralized logging, metrics, distributed tracing, and dashboards to diagnose production failures.
Manage LLM operational requirements including model gateways, rate limits, and runtime isolation.
Validate operational readiness and maintain deployment standards and runbooks for engineering teams.
Automate operational workflows using Python or Bash to troubleshoot distributed systems.
What we're looking for
Bachelor’s degree and 8+ years of experience building and operating production infrastructure in AWS and Databricks.
9+ years of experience building and operating production infrastructure in AWS and Databricks in lieu of a degree.
Experience with Infrastructure-as-Code, containers, orchestration, and CI/CD pipelines using tools like Terraform or CloudFormation.
Experience applying site reliability engineering practices including service objectives, alerting, incident response, capacity planning, and disaster recovery.
Experience implementing centralized logs, metrics, distributed traces, and dashboards to diagnose production failures.
Experience operating model gateways or AI workloads and implementing LLMOps practices.
Ability to automate operational workflows using Python or Bash and troubleshoot distributed systems.
Experience with FinOps, automated recovery, performance testing, or secure enterprise environments (preferred).