Senior Software Engineering Manager (AI Infrastructure)

Location: Santa Clara, United States; hybrid

Company

hirify.global develops AI infrastructure and distributed memory and storage platforms for large-scale LLM inference across GPU clusters.

What you will do

• Lead, mentor, and grow geographically distributed software engineering teams and technical leaders.
• Define and execute the technical strategy and roadmap for the KV Cache Platform.
• Drive the architecture, development, and delivery of distributed systems for AI inference, GPU memory optimization, distributed caching, RDMA networking, GPUDirect Storage, and NVIDIA BlueField DPUs.
• Own engineering execution, including feature development, release planning, bug triage, production issues, customer escalations, and cross-functional delivery.
• Partner with Product Management, Sales, Customer Engineering, NVIDIA, strategic technology partners, and executive leadership on customer requirements, POCs, product direction, and deployments.
• Establish practices for software quality, observability, automation, performance, testing, and production readiness.

Requirements

• 15+ years of experience building distributed systems, cloud infrastructure, storage platforms, or AI infrastructure software.
• 7+ years leading high-performing software engineering organizations, including geographically distributed teams.
• Experience delivering large-scale distributed infrastructure products from architecture through production deployment.
• Strong background in distributed systems, Linux, networking, performance engineering, and cloud-native architectures.
• Hands-on programming experience with Go and Python.
• Experience with AI infrastructure, LLM serving platforms, distributed caching, high-performance storage, HPC, networking, or enterprise infrastructure software.

Nice to have

• Experience with C or C++.
• Experience with NVIDIA Dynamo, TensorRT-LLM, Triton, RDMA, GPUDirect Storage, BlueField DPUs, Kubernetes, or related AI infrastructure.
• Experience working with strategic customers, technology partners, OEMs, or hyperscalers to deliver enterprise AI solutions.

Culture & Benefits

• Technical leadership role focused on engineering excellence, innovation, ownership, and collaboration.
• Opportunity to shape AI infrastructure product strategy and support customer deployments.
• Collaboration across engineering, infrastructure, hardware, product, sales, customer engineering, and technology partner organizations.