Stff MLE - Kubernetes Operators

Requirements:

• Experience leveraging or critically thinking about how to integrate AI into engineering and platform work—AI-powered tooling, automated operational workflows, agentic systems for fleet visibility and operations, or reasoning about AI's impact on how infrastructure is built and run.
• 8+ years of experience designing, building, and operating large-scale distributed systems and cloud-native platforms in production environments.
• Demonstrated experience building and operating Kubernetes platform infrastructure at scale, with ownership of platform capabilities through deployment, upgrades, and production operations.
• Hands-on experience developing Kubernetes Operators, Admission Controllers, or other platform extensions using Kubebuilder, Operator Framework, or similar technologies.
• Experience operating both managed Kubernetes services (EKS, AKS, GKE) and self-managed Kubernetes environments.
• Experience supporting cloud-native database platforms, large-scale data infrastructure, or stateful services on Kubernetes.
• Strong software engineering expertise in Go, with hands-on experience developing Kubernetes Operators, Controllers, Custom Resource Definitions (CRDs), and platform automation capabilities.
• Deep understanding of Kubernetes architecture, including orchestration, scheduling, security, storage, networking, and workload management.
• Proven experience operating stateful and distributed workloads on Kubernetes, including databases, data services, or other mission-critical platform components.
• Experience with public cloud platforms (AWS, Azure, or GCP), including compute, networking, security, and identity management services.
• Strong background designing and building microservices, event-driven systems, and distributed application architectures.
• Experience owning complex technical initiatives end-to-end, from architecture and design through implementation, deployment, and operational support.
• Hands-on experience with containers, CI/CD, GitOps practices, and Infrastructure-as-Code using tools such as Terraform, Crossplane, or equivalent technologies.
• Experience implementing observability and reliability best practices, including metrics, logging, tracing, monitoring, alerting, and service-level objectives.
• Proven ability to drive technical strategy through architectural design reviews, technical proposals, and cross-functional collaboration.

Good to have:

• Experience with container networking (CNI) and/or service mesh.
• Experience with mTLS, workload identity, and secrets management at fleet scale.
• Experience with observability—metrics, tracing, and SLOs.
• Experience with Terraform, Crossplane, or similar declarative infrastructure tooling.
• Experience designing or tuning distributed data or compute workloads on Kubernetes.

Distributed Systems Expertise:

• Experience with large‑scale deployments of distributed systems.
• Deep knowledge of replication, fault-tolerant, and HA strategies.
• Experience working in DevOps environments to operationalise distributed platforms.
• Strong expertise in designing and architecting platforms using:
• Kubernetes (workload deployments, upgrades, monitoring and maintenance)
• Apache Kafka (high‑scale clusters, topic/partition strategies, HA) is a plus
• Redis (high‑scale clusters, HA) is a plus
• Expertise in data formats such as Parquet, ORC, and Avro, along with compaction and governance strategies.
• Ability to build scalable, fault‑tolerant ingestion and transformation workflows.