Platform and Reliability Engineer, Senior Manager

Booz Allen Hamilton•McLean, VA

8d•$142,900 - $266,000

About The Position

Build and operate the secure, reliable foundation for enterprise agentic AI. The role provides cloud infrastructure, shared runtimes, model access, deployment pipelines, and observability services that enable engineering teams to deliver and operate AI solutions. The engineer automates environments and security controls; monitors availability, latency, throughput, token consumption, and cost; and leads shared-platform incident response and recovery. In collaboration with AI engineering, data engineering, and forward-deployed engineering, the role validates operational readiness and maintains deployment standards and runbooks. Accountability centers on shared platform reliability, security infrastructure, and production operations. U.S. citizenship is required due to the nature of work performed within the facility.

Requirements

9+ years of experience building and operating production infrastructure in AWS, Azure, or Google Cloud, including networking, identity, secrets management, and access controls.
Experience with Infrastructure-as-Code, containers, orchestration, and CI/CD pipelines, including automated security and deployment checks.
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 and performance issues.
Knowledge of LLM operational requirements, including model gateways, rate limits, retries, timeouts, runtime isolation, and consumption costs.
Ability to automate operational workflows using languages such as Python or Bash, and troubleshoot distributed systems.
Ability to document support responsibilities, evaluate readiness evidence, and coordinate technical handoffs across teams.
Bachelor’s degree.
U.S. citizenship is required.

Nice To Haves

Experience with Kubernetes, Terraform, OpenTelemetry, LangSmith, Langfuse, or comparable tools.
Experience operating model gateways or AI workloads, and implementing LLMOps practices.
Experience with FinOps, automated recovery, performance testing, or secure enterprise environments.

Responsibilities

Build and operate cloud infrastructure and shared services supporting enterprise agentic AI.
Automate environments and security controls.
Monitor platform availability, latency, throughput, token consumption, and cost.
Lead shared-platform incident response and recovery.
Collaborate with AI engineering, data engineering, and forward-deployed engineering teams.
Validate operational readiness and maintain deployment standards and runbooks.
Document support responsibilities, evaluate readiness evidence, and coordinate technical handoffs across teams.