Staff Engineer – Platform (R6019)

About the role

Shield AI is seeking a Staff Platform Engineer to design and operate the core infrastructure that powers Forge, its AI Factory. The role focuses on building scalable, reliable, and secure platform services that enable autonomous system development across cloud, on‑premises, edge, and air‑gapped environments.

Key responsibilities

• Design, develop, and operate Kubernetes‑native services, controllers, and operators that support distributed workloads in multiple environments.
• Create reusable primitives for authoring, scheduling, and scaling complex data‑processing pipelines.
• Build robust data‑storage, ingestion, validation, and transformation capabilities to support large‑scale AI training data.
• Implement platform components for authentication, authorization, networking, secret management, and observability.
• Define reference architectures, deployment patterns, capacity guidance, and benchmarks for cloud, on‑prem, edge, and air‑gapped deployments.
• Establish end‑to‑end metrics, logs, traces, dashboards, alerts, SLOs, and runbooks to ensure operational reliability.
• Collaborate with autonomy, ML‑Ops, simulation, test, infrastructure, and product teams to turn recurring challenges into reusable platform features.

Required profile

• Extensive experience designing and operating production‑grade distributed systems, cloud‑native platforms, or data‑intensive services.
• Proven ability to deliver production software in Go and Python.
• Deep understanding of distributed‑system fundamentals such as failure handling, idempotency, consistency trade‑offs, retries, ordering, backpressure, partitioning, state management, and fault tolerance.
• Experience with workflow orchestration, distributed job execution, asynchronous processing, or event‑driven architectures.
• Hands‑on expertise in troubleshooting, performance analysis, and reliability improvement while defining architectural standards.
• Strong technical communication skills to convey complex architecture to both specialists and downstream users.

Required skills

• Go
• Python
• Kubernetes (controllers, operators, CRDs)
• Cloud‑native platform design
• Distributed systems engineering
• Workflow orchestration (e.g., Argo, Temporal, Ray)
• Event‑driven data pipelines
• Observability tools (OpenTelemetry, Prometheus, Grafana, Jaeger)
• Infrastructure as Code (Terraform, Helm, ArgoCD)