Technical Program Manager

Responsibilities

• Drive end-to-end execution of large-scale, cross-functional programs spanning inference engines, training frameworks, and hardware integration
• Define program structure, including milestones, dependencies, critical paths, risks, and success criteria
• Run design reviews, sprint planning, release readiness reviews, and post-mortems
• Identify and unblock cross-team dependencies across kernel, runtime, scheduler, networking, and model teams
• Drive release management for major versions, including changelog ownership and partner rollout sequencing
• Partner with Product Management to translate roadmap priorities into executable program plans
• Coordinate hardware enablement programs with partners like Nvidia, Google, and AWS
• Build and improve engineering operating cadence, including OKR tracking and reporting to leadership
• Lead incident response coordination for production issues and own root-cause reviews

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
• 4+ years of experience in Technical Program Management, Engineering Management, or a senior engineering role
• Strong technical fluency in systems software, distributed systems, or AI/ML infrastructure
• Demonstrated track record shipping complex, multi-team programs on time
• Excellent written and verbal communication skills

Preferred Qualifications

• Direct experience shipping AI/ML infrastructure (inference engines, training frameworks, GPU kernels)
• Hands-on coding background in Python, C++, or CUDA
• Experience coordinating with hardware vendors like Nvidia, AMD, or Google TPU
• Experience driving open-source release programs or working in OSS communities
• Familiarity with CI/CD systems and observability tooling for distributed systems
• Experience supporting B2B or developer-facing products with enterprise SLAs

About the Company

RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems, created SGLang, and developed Miles. We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training.