Partner closely with Product Management, Sales, Customer Engineering, NVIDIA, and strategic technology partners to prioritize customer requirements, drive proof-of-concepts (POCs), influence product direction, and successfully deliver customer deployments.
Own day-to-day engineering execution, including feature development, release planning, bug triage, production issues, customer escalations, and cross-functional execution to ensure timely, high-quality software delivery.
Establish engineering best practices for software quality, observability, automation, performance, testing, and production readiness.
Collaborate across engineering, infrastructure, and hardware teams to deliver scalable, production-ready AI infrastructure while developing future engineering leaders and driving continuous improvement.
QUALIFICATIONS
REQUIRED
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.
Proven 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 C/C++ is a plus.
Demonstrated ability to lead cross-functional initiatives and influence technical direction across multiple organizations.
Experience building AI infrastructure, LLM serving platforms, distributed caching systems, or high-performance storage solutions.
Experience with technologies such as NVIDIA Dynamo, TensorRT-LLM, Triton, RDMA, GPUDirect Storage, BlueField DPUs, Kubernetes, or related AI infrastructure.
Background in HPC, distributed storage, networking, or enterprise infrastructure software.
Experience working directly with strategic customers, technology partners, OEMs, or hyperscalers to deliver enterprise AI solutions.
