Senior Software Engineering Manager – KV Cache Platform

DDN
Santa Clara Colocation, US
Hybrid

Who this role is best for

Best suited to experienced distributed systems leaders with a background in AI infrastructure working in geographically dispersed environments.

Best fit for

  • Experienced distributed systems leaders with a background in AI infrastructure
    — “building highly scalable, low-latency distributed systems that power AI inference”
  • Candidates who have led geographically distributed engineering teams and delivered large-scale infrastructure products
    — “7+ years leading high-performing software engineering organizations, including geographically distributed teams”
  • Individuals with hands-on programming experience in Go and Python and familiarity with AI-specific technologies
    — “Hands-on programming experience with Go and Python; experience with C/C++ is a plus”

Things to consider

  • This role requires a long-term commitment to building and leading an engineering organization
    — “This is a highly visible leadership role with responsibility for engineering execution, customer success, roadmap delivery”
  • Significant cross-functional collaboration is expected across multiple teams and strategic partners
    — “Partner closely with Product Management, Sales, Customer Engineering, NVIDIA, and strategic technology partners”

How to stand out

  • Highlight your experience in delivering AI infrastructure from architecture to production deployment
    — “Proven experience delivering large-scale distributed infrastructure products from architecture through production deployment”
  • Emphasize your ability to influence product direction and lead cross-functional initiatives
    — “Demonstrated ability to lead cross-functional initiatives and influence technical direction across multiple organizations”
  • Showcase your background in HPC, distributed storage, or enterprise infrastructure software
    — “Background in HPC, distributed storage, networking, or enterprise infrastructure software”
  • Demonstrate your technical depth in distributed systems, Linux, and cloud-native architectures
    — “Strong background in distributed systems, Linux, networking, performance engineering, and cloud-native architectures”
  • Position yourself as a leader with direct experience in working with strategic customers and technology partners
    — “Experience working directly with strategic customers, technology partners, OEMs, or hyperscalers to deliver enterprise AI solutions”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • customer success
  • roadmap delivery
Typical background
software engineering managementAI infrastructure

Skills & requirements

Required

Distributed SystemsAI InfrastructureTechnical Leadership

Preferred

Nvidia TechnologiesHPC

Stack & domain

Distributed SystemsCloud InfrastructureStorage PlatformsAI InfrastructureGoPythonC/c++KubernetesNvidia DynamoTensorrt-llmTritonRDMAGpudirect StorageBluefield DpusLeadershipCommunicationTeamworkCollaborationSoftware EngineeringAICloud Computing

About the role

Original posting from DDN via Ashby

DDN is seeking a Senior Software Engineering Manager to lead the engineering organization responsible for our KV Cache Platform—a distributed memory and storage platform that accelerates large-scale LLM inference across GPU clusters.

In this role, you will lead geographically distributed engineering teams responsible for building highly scalable, low-latency distributed systems that power AI inference. You will define the technical vision and execution strategy for the platform while partnering closely with Product Management, Sales, Customer Engineering, NVIDIA, and executive leadership to deliver innovative AI infrastructure that meets customer needs and supports DDN's long-term product strategy.

This is a highly visible leadership role with responsibility for engineering execution, customer success, roadmap delivery, and building a world-class engineering organization.

RESPONSIBILITIES

  • 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.

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.

Source: DDN careers (Ashby)

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