Staff Platform Engineer — Kubernetes-native Systems

F7d8749a; San Diego (CA); Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

Shield AI in San Diego is seeking a Staff Platform Engineer to lead Forge Platform engineering, shaping architecture, production software, and reusable patterns across cloud, on-prem, and edge environments. You will drive capabilities that support autonomous workloads, data processing, and scalable workflows for AI pilots.

You will partner with autonomy, ML, simulation, test, infra, and product teams to design Kubernetes-native services, data pipelines, and observability, balancing developer

Qualifications

• Significant experience designing and operating production distributed systems.
• Strong software engineering skills in Go and Python with production experience.
• Deep understanding of failure handling, idempotency, and fault tolerance.
• Experience with workflow orchestration or distributed job execution.
• Ability to define architecture and standards while coding.
• Proven ability to collaborate across multiple teams.

Responsabilités

• Build Kubernetes-native platform services, controllers, operators, and deployment patterns.
• Develop distributed orchestration capabilities for scheduling and scaling pipelines.
• Create reliable data-processing infrastructure for storage, ingestion, validation, and transformation.
• Develop extensible platform components around auth, observability, networking, and secrets.
• Establish reference architectures and deployment patterns across cloud/on-prem/edge.
• Improve observability and operability with metrics, logs, dashboards, and runbooks.
• Collaborate with autonomy, ML Ops, simulation, test, infra, and product teams to turn recurring problems into reusable platform capabilities.

Connaissances

Distributed systems

Go

Python

Cloud-native

Production systems

Leadership

Observability

Communication

Cross-team collaboration

Description du poste

Shield AI in San Diego is seeking a Staff Platform Engineer to lead Forge Platform engineering, shaping architecture, production software, and reusable patterns across cloud, on-prem, and edge environments. You will drive capabilities that support autonomous workloads, data processing, and scalable workflows for AI pilots.

You will partner with autonomy, ML, simulation, test, infra, and product teams to design Kubernetes-native services, data pipelines, and observability, balancing developer