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Senior Cloud Infrastructure Engineer, Google Public Sector

Google3,228 open roles

Where
Reston, VA, USA; Washington D.C., DC, USA
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Your applicationOpen nowSenior Cloud Infrastructure Engineer, Google Public SectorGoogle · Reston, VA, USA; Washington D.C., DC, USA
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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 30 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: first seen 23 minutes ago

Google median: 30 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Must be a US Citizen to meet customer and compliance requirements, including potential access to classified information.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Reston, VA, USA; Washington D.C., DC, USA.

Minimum qualifications:

  • Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical engineering experience.
  • 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 (SRE) practices, including SLIs/SLOs, distributed tracing, observability systems (e.g., Prometheus, Grafana, OpenTelemetry), and incident response.
  • Experience with Infrastructure as Code (IaC) and configuration management using declarative tools such as Terraform, OpenTofu, or Pulumi.
  • Experience orchestrating containerized workloads using Kubernetes, and 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.

Preferred qualifications:

  • 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 (e.g., GCP) 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 leveraged in multi-agent systems (e.g., Kafka, NATS, Redis, RabbitMQ).
  • Experience engineering solutions within high-assurance compliance frameworks (e.g., DoD IL5/IL6, FedRAMP High, NIST SP 800-53, or ICD 503).

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As an Infrastructure Software Engineer (SRE/Platform), you will design, automate, and scale mission-critical platform infrastructure across Google Cloud Platform (GCP), multi-cloud, and secure air-gapped environments. You will architect high-resilience systems capable of dynamically orchestrating and scaling AI agent swarms, initially driving advanced, AI-powered cybersecurity workloads with immediate operational impact. Beyond this initial focus, you will serve as a versatile engineering team broadly deployable across our greater mission delivery portfolio to handle evolving national security and enterprise challenges.

This role may require travel up to 25% of the time.

Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Architect, implement, and maintain resilient, self-healing platform infrastructure across Google Cloud Platform (GCP) and hybrid environments, establishing declarative Infrastructure as Code and git-driven deployment workflows.
  • Develop orchestration layers and high-concurrency runtime environments capable of provisioning, scaling, and terminating dynamic AI agent swarms on demand, optimizing for rapid elasticity, GPU/compute utilization, and cost efficiency.
  • Establish and advocate Service-Level Objectives/Indicators (SLOs/SLIs), and error budgets across all distributed services, implementing comprehensive distributed tracing, metrics, and automated alert systems to guarantee system availability and fault tolerance.
  • Eliminate operational toil through software engineering by building custom internal tooling, operators, controllers, and self-remediating pipelines, while executing chaos experiments to proactively expose systemic bottlenecks.
  • Adapt core platform modules to operate reliably across secondary cloud providers and restricted, air-gapped, or on-premises enterprise environments without sacrificing developer velocity or security boundaries.
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