Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.
Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.
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:
Business Insider named us an “enterprise startup to bet your career on”
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
Quartz ranked us the #1 best company for remote workers
We're looking for a hands-on Platform/Observability Engineer to join our infrastructure team. You'll own and evolve our observability stack - from logging pipelines and tracing to metrics and alerting - across a multi-datacenter, Kubernetes-based environment. This is a production-first role: you'll be expected to ship, iterate, and improve systems under real delivery pressure, not just design them on paper.
You'll work closely with other infra and product engineering teams to improve observability coverage, reduce operational toil, and help the broader organization adopt better practices.
Tech Stack Highlights: OpenTelemetry · Kafka · Vector · VictoriaMetrics · EKS · Kubernetes · Logging pipelines · Distributed tracing · SPM· AWS
Designing, deploying, and maintaining production observability stacks (logs, metrics, traces)
Scaling observability infrastructure across multiple data centers and Kubernetes clusters
Owning logging pipeline architecture and refactoring efforts
Improving distributed tracing coverage and driving adoption across engineering teams
Managing EKS upgrades, node exporters, agents, and collectors
Automating operational tasks to reduce toil and improve system stability
Contributing to compliance and audit readiness (access controls, data handling, pipeline integrity)
Evaluating and adopting new observability tooling - knowing what's worth pursuing and what isn't
Solid hands-on production experience with observability systems
Strong plus - familiarity with OpenTelemetry, Kafka, Vector, and VictoriaMetrics (vmagent, alerting rules)
Experience with logging pipelines: design, deployment, and refactoring
Understanding of distributed tracing and SPM (Service Performance Monitoring) built on top of tracing
Experience with Kubernetes cluster lifecycle management (EKS preferred)
Practical knowledge of storage trade-offs for observability data at scale
Experience using AI to automate infrastructure or observability tasks (e.g., automated RCA, PR generation, deployment workflows)
Familiarity with AI-assisted tooling selection and workflow integration
Experience with MCP (custom or open-source implementations)
Background in cloud account or environment migrations
Understanding network architecture, troubleshooting and incident resolution skills in Production environment, writing Post-mortems.
Experience with containers and Kubernetes (installation and configuration of operators).
Basic knowledge of one or more high-level programming languages, such as Python, Golang, Java
Good communication and collaboration skills in international technological companies.
Interest in modern big distributed storage technologies, architectures.
Good Spoken English to participate in product-related, architectural and technical discussions.
Proper balance between being hands-on and deeper analytical approaches