Staff Engineer (Platform)

Join our team as a Staff Platform Engineer, where you will play a crucial role in developing and operating Kubernetes-native platform services, designing distributed orchestration capabilities, and building reliable data-processing infrastructure. You will also create reference architectures, advance observability and operability, and partner with downstream teams to turn recurring distributed-systems problems into reusable platform capabilities. This is a hands-on technical leadership role that requires significant experience in designing and operating production distributed systems, cloud-native platforms, and backend infrastructure.

Contribuer à la conception et à l'implémentation de solutions et d'infrastructures de plateforme qui alimentent Forge, l'usine d'IA.

Responsibilities

• Développer et exploiter des services basés sur Kubernetes, des contrôleurs, des opérateurs, des modèles de déploiement et des intégrations d'exécution.
• Collaborer avec des équipes interfonctionnelles pour transformer les problèmes récurrents des systèmes distribués en capacités de plateforme réutilisables.
• Significant experience designing and operating production distributed systems, cloud-native platforms, backend infrastructure, or data-intensive services
• Ability to define architecture and technical standards while remaining hands-on in implementation, production troubleshooting, performance analysis, and reliability improvement
• Service networking technologies and practices such as Envoy, service meshes, Kubernetes networking, and CNI plugins

Requirements

• Clear technical communication and the ability to make complex distributed-systems architecture understandable to both specialists and downstream users
• Experience working across multiple teams to turn recurring infrastructure needs into reusable, well-documented platform capabilities
• Experience designing or operating workflow orchestration, distributed job execution, asynchronous processing, event-driven systems, or long-running service workflows
• Strong software engineering skills and a record of delivering production systems in Go and Python
• Deep understanding of distributed-systems fundamentals, including failure handling, idempotency, consistency tradeoffs, retries, ordering, delivery semantics, backpressure, partitioning, state management, and fault tolerance
• Kubernetes controllers, operators, Custom Resource Definitions, admission control, scheduling extensions, KubeRay, or workload-management systems
• Distributed execution and workflow technologies such as Ray, Temporal, Argo Workflows, Flyte, Dagster, Airflow, Prefect, Kubernetes Jobs, or comparable systems
• Durable messaging and event-streaming technologies such as NATS JetStream, Kafka, Redpanda, Pulsar, RabbitMQ, SQS/SNS, or comparable systems
• ETL/ELT, batch processing, event-driven data pipelines, CDC, schema evolution, data validation, artifact processing, or large-file transfer workflows
• Observability software such as OpenTelemetry, Prometheus, Grafana, Loki, Tempo, Jaeger, distributed tracing, structured logging, SLOs, service-level indicators, alerting, and incident-management practices

Preferred

• Terraform, Helm, ArgoCD, GitOps, Kubernetes package management, repeatable platform distribution, and Infrastructure as Code

Pay

USD 190,000 - 290,000