Kevala Logo

Kevala

Staff Site Reliability Engineer

Reposted One Month Ago
In-Office or Remote
Hiring Remotely in San Francisco, CA, USA
136K-180K Annually
Senior level
In-Office or Remote
Hiring Remotely in San Francisco, CA, USA
136K-180K Annually
Senior level
The Staff Site Reliability Engineer will lead in designing and maintaining cloud infrastructure on GCP, drive IaC strategy, manage Kubernetes operations, ensure security compliance, and mentor engineers.
The summary above was generated by AI

As a Staff Site Reliability Engineer, you will be a key technical leader responsible for the architecture, reliability, and security of our entire cloud infrastructure. You will drive technical direction, mentor engineers, and solve our most complex infrastructure challenges as a hands-on contributor.

You will lead the management of our Google Cloud Platform (GCP) environment, drive our Infrastructure as Code (IaC) strategy, and ensure our Kubernetes-based microservices are deployed seamlessly and securely. You will serve as the expert for scalability, observability, and building the robust, automated systems that power Kevala's continuous deployment pipeline.

The applicant must have current, unrestricted work authorization in the United States. This job is not eligible for visa sponsorship.

What you will be doing

  • Architect & Maintain: Design, build, and maintain our core cloud-native infrastructure on Google Cloud Platform (GCP) following established best practices.
  • Infrastructure as Code (IaC): Lead our IaC strategy, writing and reviewing high-quality Terraform to manage all cloud resources in a repeatable and version-controlled way.
  • Kubernetes Operation: Manage and scale our Google Kubernetes Engine (GKE) clusters, including configuration of ingress, and monitoring components.
  • Champion Security & Compliance: Integrate, implement, and audit security best practices across all infrastructure layers (GCP IAM, GKE policies, network security), ensuring regulatory compliance and leading incident response.
  • Database Reliability: Manage the provisioning, scaling, and reliability of our Postgres databases (e.g., Cloud SQL) and other data stores.
  • Observability: Build and refine our monitoring, tracing, logging, and alerting systems (e.g., OpenTelemetry, Grafana, Google Cloud's operations suite) to ensure high availability.
  • Mentorship and Design: Partner with engineering teams on scalable architecture design. Mentor other engineers on DevOps practices, cloud architecture, and security.

What you need to succeed

  • Experience: 8+ years in a SRE, DevOps, or Infrastructure Engineering role, with a proven track record of operating in a Staff or similar technical leadership capacity.
  • Leadership & Communication: Excellent communication skills with the ability to clearly articulate complex technical decisions, mentor team members, and drive projects to completion.
  • GCP Proficiency: Extensive hands-on experience designing and managing production environments in Google Cloud Platform.
  • Kubernetes (K8s) Expert: Advanced knowledge of Kubernetes and its ecosystem (GKE preferred), including cluster administration and deployment tooling (e.g., Helm).
  • Terraform/IaC: Extensive, production-level experience using Terraform to manage complex cloud environments.
  • Automation: Deep experience with automation tooling and scripting (e.g., Bash, Python, Go) to manage infrastructure and operations at scale.
  • Database Skills: Experience managing and scaling relational databases like Postgres in a production environment.
  • Security Implementation & Auditing: Practical experience designing, implementing, and auditing security controls for cloud infrastructure, networks, and applications (e.g., IAM, network security).

The compensation for this opportunity includes a base salary range of $ 136,000 - $ 180,000, plus equity (stock options). This is our target compensation range and is subject to multiple factors, including level, experience, and location. As you go through our interview process, our recruiter will work with you to identify a competitive base salary within the proposed range and combine it with an equity package that reflects your excitement about joining Kevala.

This is a fully remote role which can be located anywhere within the United States. Please note that actual salaries may vary based on factors including, but not limited to, education, experience, and location.

HQ

Kevala San Francisco, California, USA Office

55 Francisco St, San Francisco, California, United States, 94133 2112

Similar Jobs

8 Days Ago
Easy Apply
Remote
United States
Easy Apply
Senior level
Senior level
Cloud • Security • Software • Cybersecurity • Automation
Build and operate reliable, scalable production infrastructure for GitLab’s user-facing services. Responsibilities include developing infrastructure automation and tooling, managing Kubernetes deployments, maintaining infrastructure as code, supporting CI/CD and GitOps, participating in on-call and incident response, improving observability and SLOs, troubleshooting production systems, and documenting operational practices. The role spans Intermediate through Senior Staff levels and requires strong software engineering, cloud, reliability, and asynchronous collaboration skills.
Top Skills: AlertingAWSCi/CdGCPGitopsGoInfrastructure As CodeKubernetesLoggingMetricsRubySlisSlosTerraform
2 Days Ago
Remote
USA
177K-240K Annually
Expert/Leader
177K-240K Annually
Expert/Leader
Information Technology • Security • Software • Cybersecurity
Lead reliability strategy across eight engineering groups by defining SLIs, SLOs, and error budgets; strengthening incident response, alerting, postmortems, change safety, and failure testing; and coaching teams to own reliability. The role remains hands-on through production investigations, tooling, dashboards, and reference implementations. It also leads AI adoption in incident management and observability while partnering with architecture, platform, and product teams to improve distributed-system resilience.
Top Skills: Ai ToolsAWSDatadogDynamoDBElasticsearchGoInfrastructure As CodeKafkaKubernetesObservability ToolingRedisTypescript
12 Days Ago
In-Office or Remote
San Francisco, CA, USA
320K-485K Annually
Senior level
320K-485K Annually
Senior level
Artificial Intelligence • Natural Language Processing • Generative AI
Own production safeguards infrastructure for Claude model launches and safety classifier deployments. Configure and verify safeguards across first-party, AWS Bedrock, and GCP Vertex platforms; lead canary rollouts, post-deployment validation, incident response, and rollback decisions. Build automation, continuous validation, repeatable deployment pipelines, and a provenance registry to reduce operational toil and configuration drift. Participate in on-call rotations and launch readiness processes.
Top Skills: AWSGCPLlm Inference SystemsMl InfrastructurePythonRustTransformer-Based Models

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account