
51 - 200 employees
💼 Consulting
🏢 Enterprise
🤝 B2B
Consulting • Enterprise • B2B
Virtasant is a cloud services and optimization company that helps businesses migrate to, manage, and build on public cloud platforms. They combine a proprietary automation platform with managed services and FinOps expertise to reduce cloud costs (claiming average savings of over 50%), support Cloud FinOps programs, and deliver outcome-based engagements rather than hourly or seat-based billing. Virtasant also provides enterprise AI guidance and partners with major cloud providers (AWS, Google Cloud, Azure) to deliver migration, optimization, and 24/7 managed operations.
🔥 0 minutes ago
Apache
AWS
Azure
Cloud
Distributed Systems
Docker
Google Cloud Platform
Grafana
GRPC
Java
Kafka
Kubernetes
Linux
Postgres
Prometheus
Python
Spark
Terraform
Vault
Go
Where this job comes from
Posted on Virtasant's careers page, not through a job board
First seen by Remote Rocketship 0 minutes ago

51 - 200 employees
💼 Consulting
🏢 Enterprise
🤝 B2B
Consulting • Enterprise • B2B
Virtasant is a cloud services and optimization company that helps businesses migrate to, manage, and build on public cloud platforms. They combine a proprietary automation platform with managed services and FinOps expertise to reduce cloud costs (claiming average savings of over 50%), support Cloud FinOps programs, and deliver outcome-based engagements rather than hourly or seat-based billing. Virtasant also provides enterprise AI guidance and partners with major cloud providers (AWS, Google Cloud, Azure) to deliver migration, optimization, and 24/7 managed operations.
• Design, build, and operate production Kubernetes clusters, including networking, workload isolation, and multi-region topologies • Build and extend infrastructure orchestration using Crossplane, Kubernetes custom resources, controllers, and operators • Develop reusable, self-service platform capabilities for engineering teams • Implement and operate service mesh capabilities, including mTLS, service-account authentication and authorization, and traffic management • Optimize containerized workloads for performance, cost, resource efficiency, and blast-radius reduction • Write, refactor, and maintain production services, Kubernetes controllers, operators, and platform middleware • Build HTTP, REST, and gRPC service interfaces • Write unit and integration tests • Lead incident response and resolve root causes of platform-level issues • Troubleshoot production Kubernetes infrastructure and distributed systems using logs, metrics, traces, and profiling tools • Define and drive SLOs and actionable alerting • Design and maintain reusable Terraform modules and Crossplane abstractions • Develop and improve Crossplane, Terraform, and GitOps provisioning workflows • Build and improve CI/CD and GitOps delivery workflows • Support cloud migration initiatives while maintaining reliability and minimizing downtime • Build and maintain metrics, dashboards, alerting policies, and distributed tracing • Instrument platform components for diagnosability • Partner with data engineering, product, security, and infrastructure teams on requirements and architecture • Contribute to design reviews and technical direction • Mentor engineers and improve platform engineering practices • Independently drive complex infrastructure initiatives and communicate decisions, trade-offs, and progress
• 7+ years of professional experience in software, platform, infrastructure, or site reliability engineering • Significant experience operating production distributed systems • Demonstrated experience building and operating production Kubernetes platforms • Production software development experience in Go, Python, or Java; Go strongly preferred • Experience building infrastructure or internal developer platforms consumed by multiple engineering teams • Experience designing, developing, and maintaining reusable Terraform modules or equivalent infrastructure abstractions • Experience independently designing systems from an ambiguous starting point through implementation and production • Degree in Computer Science, Engineering, or a related field, or equivalent practical experience • Strong understanding of Kubernetes internals, including CNI networking, NetworkPolicy, resource management, scheduling, cluster lifecycle, and behavior under load • Hands-on experience with Kubernetes APIs, custom resources, controllers/operators, and reconciliation patterns • Experience with declarative infrastructure orchestration and provisioning; Crossplane highly preferred • Infrastructure as Code at scale, particularly Terraform module design and ownership • Strong understanding of GitOps practices, preferably with Argo CD • Hands-on experience with a service mesh such as Istio, Envoy, or Linkerd, including mTLS and workload identity • Solid Linux fundamentals, including cgroups, networking, and resource management • Production experience with at least one major cloud platform: GCP, AWS, or Azure • Observability tooling experience with Prometheus, Grafana, OpenTelemetry, and query languages such as PromQL • Production experience with relational databases, including PostgreSQL or managed Postgres-compatible services • Docker and container tooling experience • Strong debugging and performance profiling skills • Preferred experience with Crossplane Compositions, XRDs, providers, managed resources, or custom infrastructure abstractions • Preferred open-source contributions to CNCF or Kubernetes ecosystem projects • Preferred experience with large-scale data platforms and Apache Kafka, Apache Flink, or Apache Spark • Preferred Alibaba Cloud experience • Preferred Kubernetes certifications such as CKA, CKAD, or KCNA • Preferred Go testing frameworks such as Ginkgo and Gomega • Preferred identity and access management experience with SSO, Keycloak, OIDC, SAML, or Vault • Preferred high availability and disaster recovery design across regions or providers • Preferred monorepo and Bazel experience • Ability to read Java • Exposure to compliance frameworks such as SOC 2 or GDPR • Strong analytical and problem-solving ability • Clear written and verbal communication • Highly autonomous and proactive • Comfortable in a fast-moving, highly technical environment
• Fully remote work arrangement • Pacific Hours (8:00 AM – 5:00 PM PST) • Opportunity to work on a large-scale data platform processing approximately 400,000 pipelines daily • Mentorship and collaboration with data engineering, product, security, and infrastructure teams
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