Senior Systems Software Engineer – NV Cloud Functions

NVIDIA

. Improve the performance, reliability, and scaling behavior of a system routing AI workloads onto distributed GPU fleets .

Posted 9/17/2026full-timeRemote • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in systems programming with a focus on performance and reliability of distributed GPU workloads. Proficient in automation and optimization of cloud-native systems, with strong collaboration skills across engineering teams.

Highest-signal resume keywords

Expert-Level Knowledge In Go, C, RustStrong Understanding Of KubernetesHands-On Automation Experience In GitLab, ArgoCDExperience Developing Kubernetes Custom ResourcesUnderstanding Of Performance And Reliability In Distributed Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

JavaGoRustData StructuresAlgorithmsDistributed Software ArchitectureBashPythonPerformance OptimizationMessage Queues

Soft Skills

CollaborationDocumentation Writing

Tools & Technologies

KubernetesGitLabArgoCDNVIDIA HardwareHTTP/2GRPC

Certifications & Qualifications

Bachelor’s Degree In Computer ScienceMaster’s Degree In Computer Science

Industry Keywords

Cloud Native SystemsDistributed GPU FleetsOpen-Source ProjectContainer OrchestrationUnix/Unix-Like Kernels

Tech Stack

Tools & technologies

CloudDistributed SystemsGRPCJavaKubernetesLinuxPythonRustUnixGo

About the role

Key responsibilities & impact

Improve the performance, reliability, and scaling behavior of a system routing AI workloads onto distributed GPU fleets
Design and ship services in Java, Go, and Rust
Build in the open on a public repository with transparent commits, design proposals, and reviews
Automate and optimize build, test, integration, and release processes for cloud native systems
Partner with engineering teams across NVIDIA to integrate adjacent technologies, including KAI Scheduler, NVIDIA NIM, Grove, and Dynamo
Triage community issues and pull requests for an open-source project
Write documentation for contributors
Develop, deploy, and monitor GPU- and DPU-accelerated applications on NVIDIA hardware

Requirements

What you’ll need

Bachelor’s or Master’s Degree in Computer Science or equivalent experience
3+ years of hands-on software engineering
Expert-level knowledge in a systems programming language (Go, C, Rust)
Proven understanding of Data Structures, Algorithms, and Distributed Software Architecture
Strong understanding of container orchestration systems (Kubernetes) and container technologies
Hands-on automation experience in continuous integration frameworks such as GitLab and ArgoCD
Expertise in a scripting language (Bash, Python)
Knowledge and experience working with system internals of Unix/Unix-like kernels such as Linux
Understanding of performance, security, and reliability in complex distributed systems
Background with pub-sub models and message queues
Experience optimizing high-throughput network paths
Working understanding of unary, streaming, and bidirectional protocols across HTTP/2 and gRPC
Experience developing Kubernetes Custom Resources and Operators deployed in Cloud Service Providers

Benefits

Comp & perks

Competitive salaries
Generous benefits package