Autonomy for the world. Backed by a16z.
About the role
This is a hands-on technical leadership role. You will define platform architecture, implement production software, establish reusable operational patterns, and partner with teams across autonomy, ML, simulation, test, infrastructure, and product engineering. Success requires balancing developer productivity, reliability, extensibility, performance, portability, and long-term operational maintainability.
What they're looking for
- Significant experience designing and operating production distributed systems, cloud-native platforms, backend infrastructure, or data-intensive services
- Strong software engineering skills and a record of delivering production systems in Go and Python
- Experience designing or operating workflow orchestration, distributed job execution, asynchronous processing, event-driven systems, or long-running service workflows
- Ability to define architecture and technical standards while remaining hands-on in implementation, production troubleshooting, performance analysis, and reliability improvement
- Experience working across multiple teams to turn recurring infrastructure needs into reusable, well-documented platform capabilities
- Clear technical communication and the ability to make complex distributed-systems architecture understandable to both specialists and downstream users
More about this role
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube .
We are looking for a Staff Platform Engineer to contribute to the Platform solutions and infrastructure that power Forge, the AI Factory. These components provide distributed runtime capabilities that enable teams to reliably orchestrate workloads, process data, and underpin the workflows of building an AI Pilot.
The Forge Platform Engineering team provides Kubernetes-native capabilities that support autonomy development, simulation, testing, training, evaluation, deployment, and operational workflows across commercial cloud, on-premises infrastructure, sovereign deployments, edge environments, and fully air-gapped systems.
This is a hands-on technical...
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