Senior Cloud Infrastructure Engineer, Google Public Sector

Google•Washington, DC

2d•$174,000 - $252,000

About The Position

As an Infrastructure Software Engineer (SRE/Platform) at Google Cloud, you will design, automate, and scale mission-critical platform infrastructure across Google Cloud Platform, multi-cloud, and secure air-gapped environments. You will architect resilient systems that dynamically orchestrate and scale AI agent swarms, initially supporting AI-powered cybersecurity workloads. You will also contribute broadly to Google Public Sector’s mission delivery portfolio, addressing evolving national security and enterprise challenges. The role may require travel up to 25% of the time. Google Cloud software engineers develop technologies across areas such as distributed computing, large-scale system design, networking, data storage, security, and artificial intelligence. Engineers work on projects important to Google Cloud, anticipate customer needs, take ownership, and may move between teams and projects as the business evolves.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical engineering experience.
At least 5 years of experience with software engineering and infrastructure, architecting and operating secure cloud platforms, and programming in Go, Python, or Rust.
Experience with Site Reliability Engineering practices, including SLIs/SLOs, distributed tracing, observability systems such as Prometheus, Grafana, or OpenTelemetry, and incident response.
Experience with Infrastructure as Code and configuration management using declarative tools such as Terraform, OpenTofu, or Pulumi.
Experience orchestrating containerized workloads using Kubernetes.
Experience with zero-trust architecture, identity and access management (IAM), public key infrastructure (PKI), secrets management, and encryption.
Must possess an active Top Secret/SCI security clearance.

Nice To Haves

Experience architecting distributed runtime environments or message-driven orchestrations to scale dynamic AI agent swarms, distributed LLM pipelines, or parallelized autonomous compute nodes.
Experience running, patching, and maintaining platform stacks across multi-cloud environments and disconnected, air-gapped, or classified SCIF environments.
Experience authoring custom Kubernetes Operators, Custom Resource Definitions (CRDs), or platform APIs to automate cluster lifecycle management.
Experience with distributed messaging, streaming, or caching layers used in multi-agent systems, such as Kafka, NATS, Redis, or RabbitMQ.
Experience engineering solutions within high-assurance compliance frameworks such as DoD IL5/IL6, FedRAMP High, NIST SP 800-53, or ICD 503.

Responsibilities

Architect, implement, and maintain resilient, self-healing platform infrastructure across Google Cloud Platform and hybrid environments, using declarative Infrastructure as Code and git-driven deployment workflows.
Develop orchestration layers and high-concurrency runtime environments to provision, scale, and terminate dynamic AI agent swarms on demand, optimizing elasticity, GPU and compute utilization, and cost efficiency.
Establish and advocate Service-Level Objectives and Indicators (SLOs/SLIs) and error budgets across distributed services; implement distributed tracing, metrics, and automated alerts to support availability and fault tolerance.
Reduce operational toil by building internal tools, operators, controllers, and self-remediating pipelines, and conduct chaos experiments to identify systemic bottlenecks.
Adapt core platform modules for reliable operation across secondary cloud providers and restricted, air-gapped, or on-premises enterprise environments while maintaining developer velocity and security boundaries.