InterSystems powers some of the world's most mission-critical healthcare, financial services, and data platforms. Our technology runs where reliability, security, and performance are not optional, and where the work directly supports organizations that depend on trusted data every day.
As Managed Services and SaaS continue to modernize, cloud engineering and Kubernetes are becoming core foundations for how we deliver resilient, automated, and scalable services globally. This role offers the opportunity to work on real production platforms, improve how services are built and operated, and help shape a modern cloud-native operating model.
This is a chance to do hands-on engineering work that matters: cloud automation, Kubernetes operations, reliability, security, and platform improvement in an environment where technical quality has meaningful business and client impact.
About the Role
We are seeking a Senior Cloud and Kubernetes Engineer to serve as a senior hands-on contributor for the build, operation, automation, and continuous improvement of InterSystems Kubernetes-based managed services and SaaS platforms.
This role is more advanced than the Kubernetes Engineer position and is intended for someone who can independently own complex platform work, lead production troubleshooting, improve engineering standards, and mentor other engineers while partnering closely with Kubernetes architects and SRE teams.
The Senior Cloud and Kubernetes Engineer will help translate architecture into reliable implementation, bring operational discipline to Kubernetes environments, and drive automation, reliability, security, and platform maturity across public cloud, private cloud, and on-premises infrastructure.
Key Responsibilities
Senior Platform Engineering and Operations
- Independently build, operate, upgrade, and improve production Kubernetes clusters across public cloud, private cloud, and on-premises environments.
- Lead complex cluster lifecycle activities including version upgrades, node pool changes, platform patching, capacity planning, and workload migration.
- Serve as an escalation point for Kubernetes issues involving cluster health, networking, ingress, storage, certificates, scheduling, resource pressure, and workload failures.
- Identify systemic platform risks and drive corrective actions that improve reliability, security, and operability.
- Partner with architects to implement platform standards, reference designs, and approved operating patterns.
Automation, GitOps, and Infrastructure as Code
- Design and maintain reusable Terraform, Helm, and GitOps automation for repeatable Kubernetes platform deployment and configuration.
- Improve CI/CD and GitOps workflows using tools such as Argo CD, Flux, GitHub Actions, GitLab, Jenkins, or Azure DevOps.
- Drive automation that reduces manual operations, improves consistency, and lowers operational risk.
- Review infrastructure and platform changes for quality, reliability, security, and maintainability.
- Contribute to automation standards, code review practices, reusable modules, and deployment patterns.
Security, Governance, and Compliance
- Implement and improve Kubernetes RBAC, namespace isolation, network policies, secrets management, certificate lifecycle management, and workload security controls.
- Partner with security teams to remediate vulnerabilities, enforce secure platform patterns, and support audit or compliance requirements.
- Support image registry controls, container scanning, admission controls, and policy-as-code practices where applicable.
- Help define practical security standards that can be consistently implemented by engineering and application teams.
Reliability, Observability, and Incident Leadership
- Lead troubleshooting of complex production incidents and coordinate with application, infrastructure, network, security, and database teams to restore service.
- Build and improve observability using Prometheus, Grafana, Loki, Fluent Bit, CloudWatch, Azure Monitor, or equivalent platforms.
- Develop actionable dashboards, alerts, and health checks that reduce noise and improve response quality.
- Participate in post-incident reviews and drive permanent corrective actions, runbook improvements, and reliability engineering practices.
- Support SLO, error budget, and capacity planning practices in partnership with SRE teams.
Mentorship and Technical Influence
- Mentor Kubernetes Engineers, DevOps engineers, and application teams on Kubernetes operations, deployment practices, and troubleshooting.
- Provide technical leadership during platform changes, migrations, incident reviews, and application onboarding.
- Contribute to internal documentation, runbooks, implementation standards, and knowledge-sharing sessions.
- Help establish a stronger engineering culture around automation, reliability, security, and operational ownership.
Required Experience and Qualifications
- Eight or more years of experience in infrastructure, cloud, DevOps, platform engineering, or SRE roles.
- Five or more years of hands-on Kubernetes experience in production environments.
- Proven experience operating Kubernetes platforms supporting mission-critical or customer-facing workloads.
- Strong hands-on experience with at least one major public cloud platform such as AWS, Azure, or Google Cloud; experience with hybrid or on-premises Kubernetes is preferred.
- Advanced experience with Terraform, Helm, GitOps, and CI/CD automation.
- Strong Linux, container runtime, Kubernetes networking, ingress, storage, and troubleshooting skills.
- Practical experience with Kubernetes security including RBAC, network policies, secrets, workload isolation, and vulnerability remediation.
- Experience leading production incident response and driving root cause analysis and corrective actions.
- Ability to mentor engineers and influence technical direction without direct management authority.
- Strong written and verbal communication skills, including the ability to explain complex platform issues to technical and non-technical stakeholders.
Preferred Experience
- Experience with Spectro Cloud, Rancher, EKS, AKS, or GKE in production.
- Experience with service mesh technologies such as Istio, Linkerd, or Cilium.
- Experience with Kubernetes backup, restore, and disaster recovery tools such as Velero, Kasten, or Stash.
- Experience implementing policy-as-code, admission controllers, container scanning, or runtime security tooling.
- Experience with SLOs, error budgets, capacity planning, performance tuning, and reliability engineering practices.
- Experience in regulated, healthcare, financial services, or compliance-driven environments.
- Experience with Python, Bash, Go, PowerShell, or similar scripting and automation languages.
- Experience supporting migrations from traditional infrastructure or virtualization platforms to Kubernetes-based operating models.
Preferred Certifications
- Certified Kubernetes Administrator
- Certified Kubernetes Security Specialist
- Certified Kubernetes Application Developer
- HashiCorp Certified Terraform Associate
- AWS Certified DevOps Engineer Professional, Azure DevOps Engineer Expert, or Google Professional Cloud DevOps Engineer
- Linux Foundation or equivalent Linux certification
About InterSystems
InterSystems, a creative data technology provider, delivers a unified foundation for next-generation applications for healthcare, finance, manufacturing, and supply chain customers in more than 80 countries. Our data platforms solve interoperability, speed, and scalability problems for large organizations around the globe to unlock the power of data and allow people to perceive data in imaginative ways. Established in 1978, InterSystems is committed to excellence through its 24×7 support for customers and partners around the world. Privately held and headquartered in Boston, Massachusetts, InterSystems has 38 offices in 28 countries worldwide. For more information, please visit InterSystems.com.
AI Disclaimer
InterSystems may use AI tools for its internal operations including administrative tasks during recruitment (e.g., organizing candidate information). InterSystems’ approach to AI is guided by the InterSystems Responsible AI Guidelines. AI is not used to make or influence hiring decisions. All decisions are made by InterSystems employees.
Candidates may use AI for CV or interview preparation, provided materials are truthful and reflect their own experience. AI tools and third-party transcription services must not be used during interviews or assessments.
