- Location
- San Francisco, California · Palo Alto, California, United States
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Experience
- 7+ years
Description
About Workato
Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com.
Why join us?
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
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Business Insider named us an “enterprise startup to bet your career on”
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Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
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Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
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Quartz ranked us the #1 best company for remote workers
Responsibilities
As a Senior Infrastructure Engineer, you’ll be part of the team responsible for the architecture, scalability, and reliability of Workato’s distributed cloud platform. You’ll design and optimize the systems that allow our services to run securely and efficiently at scale. This is a highly technical role that requires deep experience with cloud infrastructure, Linux internals, and large-scale distributed systems.
In this role, you will also be responsible to:
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Design, build, and maintain a global, distributed, and resilient cloud infrastructure.
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Collaborate with AI engineering and iPaaS engineering teams to plan and deliver complex platform initiatives.
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Patch and optimize open-source components for performance and security.
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Build iPaaS and AI infrastructure at scale and cross-cloud.
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Manage and provision AWS infrastructure using Terraform and Kubernetes.
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Write and maintain Kubernetes manifests and deployment configurations for critical workloads.
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Improve and maintain CI/CD pipelines for scalable and secure component delivery.
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Tune Linux systems and open-source software for high performance and hardened security.
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Build internal tools to streamline engineering workflows and operational automation.
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Participate in architecture reviews, incident response, and performance analysis to ensure system reliability.
Requirements
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7+ years of experience in infrastructure or systems engineering roles.
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Proven expertise in distributed systems and cloud-native architectures.
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Strong understanding of Linux internals, including networking and system-level performance tuning.
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Experience operating infrastructure on AWS at scale.
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Proficiency with Terraform, Kubernetes.
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Solid understanding of network security and cloud security best practices.
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Hands-on experience optimizing CI/CD workflows and automating deployments.
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Excellent analytical, troubleshooting, and communication skills.
Nice to Have
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Experience with Golang for tooling or internal services.
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Experience building cross-cloud AI infrastructure.
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Familiarity with Kafka, Redis, ClickHouse, PostgreSQL, or similar technologies.
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Experience with observability tools such as Grafana, Prometheus, or VictoriaMetrics.
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Understanding of Vault or other secrets management systems.
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Contributions to or maintenance of open-source infrastructure projects.
Tech Stack
- AWS • Terraform • Kubernetes • LiteLLM • Quadrant • ArgoCD • Kafka • PostgreSQL • Redis • ClickHouse • Grafana • VictoriaMetrics • Vault