Senior Site Reliability Engineer

Responsibilities

• Own the Kubernetes footprint across development, CI, pre-production, and one customer-facing production region — local kind clusters, shared dev and QA environments, and multi-cluster/multi-region topologies.
• Operate your production region against defined SLOs: capacity and upgrade planning, patching, backup and restore, disaster recovery drills, and participation in an on-call rotation.
• Lead incident response for your region — detection, mitigation, customer-impact assessment, root-cause analysis, and blameless postmortems that feed fixes back into the platform.
• Build and maintain Helm charts and umbrella releases for the platform's services and dependencies, including versioning, values hygiene, and upgrade paths.
• Own the CI/CD pipelines end to end — build, test, image publishing, chart packaging, release cutting, and hotfix/backport flows.
• Automate environment bootstrap and seeding so any engineer can bring up a full stack — control plane, identity, gateway, database, workflow engine — with one command.
• Operate and troubleshoot the supporting stack across test and production: PostgreSQL, Temporal, Keycloak, API gateway, message broker, and observability components.
• Build observability and diagnostics — metrics, dashboards, alerting, log and audit access — that serve both engineering environments and production operations.
• Consult with product teams and with the teams operating our larger regions on deployment topology, GPU and resource scheduling, RBAC, networking, and failure modes; validate upgrade and migration procedures and hand over runbooks.
• Enforce security and tenant isolation in production: least-privilege access, secret handling, certificate and TLS lifecycle, image and dependency scanning, and audit evidence for compliance reviews.
• Drive infrastructure as code and repeatability — no snowflake environments, no undocumented manual steps.
• Mentor engineers on Kubernetes and operational practice, and raise the team's bar through review and documentation.

Requirements

• 10+ years in DevOps, SRE, platform, or infrastructure engineering, including production ownership of customer-facing Kubernetes environments.
• We expect deep production experience in several of these, and the engineering fundamentals to learn the rest rapidly.
• Kubernetes at scale, Cluster API, controllers/operators, Docker, and Helm chart authoring and lifecycle management.

Expert-level Kubernetes

workloads, networking, storage, RBAC, resource management, CRDs and operators, and cluster upgrades — able to debug from kubectl and cluster internals rather than dashboards alone. Proven incident response under SLA pressure — on-call rotations, escalation paths, postmortems, and follow-through on corrective action. Strong CI/CD engineering — pipelines as code, reproducible builds, artifact and release management (GitHub Actions or equivalent). Solid scripting and automation ability, and enough Go familiarity to read service code, trace a failure into it, and file a precise bug. Experience running the stateful supporting stack — relational databases, identity providers, gateways, and message brokers — in Kubernetes, including backup, restore, and upgrade. Track record as a technical consultant to other engineering teams: clear runbooks, design feedback, and incident write-ups across global time zones (strong written English).

Delivery

GitHub Actions or equivalent CI/CD, container registries, versioned release and backport workflows.

Infrastructure as Code

Terraform, Ansible, or equivalent, plus GitOps tooling (Argo CD, Flux).

Identity & API Management

Keycloak and API gateway operation — routing, plugins, TLS, rate limiting.

Data & Messaging

PostgreSQL operations and migrations, plus streaming/message-broker platforms (Kafka or equivalent).

Observability

Prometheus, Grafana, centralized logging, and alerting tied to SLOs.

Cloud

AWS— networking, IAM, load balancing, and managed Kubernetes Nice to Have k0s or k0rdent ecosystem experience. GPU infrastructure on Kubernetes — device plugins, node feature discovery, scheduling and sharing of accelerators. Temporal operations — namespaces, workers, schema upgrades. Bare-metal provisioning (Metal³ / BareMetalHost) or on-prem/OpenStack environments. Multi-region topologies, service mesh, or cross-cluster networking. Python for test harnesses and automation; experience with pytest-based E2E suites. Load and performance testing of API platforms. Policy enforcement (OPA/Kyverno), secret management, and pen-test remediation. OpenTelemetry, distributed tracing, or formal SLO/error-budget practice. Compliance exposure — SOC 2, ISO 27001, or similar audit support. CNCF open-source contributions.

Education and Experience

Bachelor’s degree in Computer Science & Engineering or related field or 10 years related experience.

What does Mirantis offer you? Work with an established Silicon Valley leader in the cloud infrastructure industry; Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies; Be a part of cutting-edge, open-source innovation; Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued; Professional development and training; Attend conferences and working groups; Company outings, happy hours, hackathons, and tech talks; Receive a competitive compensation package with a strong benefits plan. We are a Leader for Container Management in G2 (#2 after AWS)!

Mirantis, an IREN company, is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment—on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. https://www.mirantis.com/