Senior Software Engineering Manager – KV Cache Platform

DDN

Senior Software Engineering Manager leading DDN’s KV Cache Platform development for large-scale AI inference systems. Overseeing engineering execution and fostering technical excellence within a distributed team.

Posted 7/9/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $220,000 - $275,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in leading geographically distributed software engineering teams while driving the architecture and delivery of scalable AI infrastructure solutions. Proficient in establishing engineering best practices and collaborating with cross-functional teams to ensure high-quality software delivery.

Highest-signal resume keywords

Distributed Systems ArchitectureAI Infrastructure DevelopmentLeadership of Software Engineering TeamsGo and Python ProgrammingCloud-Native Architectures

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Distributed SystemsCloud InfrastructureAI Infrastructure SoftwarePerformance EngineeringLinuxNetworkingGo ProgrammingPython ProgrammingC/C++ ProgrammingKubernetes

Soft Skills

MentoringCollaborationInfluencing Technical DirectionCustomer EngagementCross-Functional Leadership

Tools & Technologies

NVIDIA DynamoTensorRT-LLMTritonRDMAGPUDirect StorageBlueField DPUs

Industry Keywords

High-Performance ComputingDistributed StorageEnterprise Infrastructure SoftwareAI SolutionsGeographically Distributed Teams

Tech Stack

Tools & technologies

CloudDistributed SystemsGoKubernetesLinuxPython

About the role

Key responsibilities & impact

Lead, mentor, and grow a geographically distributed team of software engineers and technical leaders, fostering a culture of technical excellence, innovation, ownership, and collaboration.
Define and execute the technical strategy and roadmap for the KV Cache Platform, ensuring scalability, reliability, security, and operational excellence.
Drive the architecture, development, and delivery of distributed systems supporting AI inference, GPU memory optimization, distributed caching, RDMA networking, GPUDirect Storage, NVIDIA BlueField DPUs, and emerging AI infrastructure technologies.
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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Health insurance
401(k) matching
Flexible work hours
Paid time off
Remote work options