Teams at Shield AI

Leads strategic Talent Acquisition and People Experience programs, including recruiting process optimization, technology implementations, change management, governance, and adoption. Partners with recruiting, HR, systems, legal, finance, IT, and business stakeholders to redesign workflows, establish operating models, manage risks and dependencies, improve candidate and hiring-manager experiences, and use data to measure outcomes and drive continuous improvement.

Build and operate Kubernetes-native platform services and distributed orchestration capabilities supporting AI workloads across cloud, on-premises, edge, sovereign, and air-gapped environments. Design production software, data-processing infrastructure, observability, deployment patterns, and operational standards. Establish reference architectures, reliability practices, benchmarks, and recovery procedures while partnering with autonomy, ML, simulation, infrastructure, and product teams. Provide hands-on technical leadership in distributed systems architecture, implementation, troubleshooting, performance analysis, and platform reliability.

Build and operate developer tools, internal platforms, development environments, project templates, and AI-enabled workflows for Hivemind engineering teams. Improve developer productivity through reusable tooling, paved paths, documentation, adoption efforts, and inner-source practices. Partner with developers to identify friction, measure outcomes using DORA metrics and feedback, and drive technical direction. Staff-level responsibilities include leading cross-team initiatives and shaping organization-wide developer productivity strategy.