Senior Systems Software Engineer - NV Cloud Functions

Team: IT

Location: India

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Design, develop, and ship scalable services using Java, Go, and Rust for a distributed GPU workload platform.
• Improve the performance, reliability, scalability, and operational behavior of systems that route AI workloads across distributed GPU fleets.
• Build and optimize cloud-native services capable of supporting inference, streaming, and batch workloads across diverse infrastructure environments.
• Develop and maintain control-plane and edge components for a distributed, open-source platform.
• Automate and optimize build, testing, integration, deployment, and release processes for cloud-native software.
• Work with Kubernetes and container technologies to develop reliable and scalable workload orchestration capabilities.
• Collaborate with engineering teams across the organization to integrate the platform with related scheduling, inference, orchestration, and AI infrastructure technologies.
• Investigate complex systems and distributed infrastructure challenges, balancing performance, security, reliability, and scalability requirements.
• Contribute to a public open-source repository through code, design proposals, technical reviews, documentation, and issue resolution.
• Triage community issues and pull requests while helping maintain a high-quality contributor experience.
• Explore new approaches for making GPU- and DPU-accelerated applications easier to develop, deploy, monitor, and operate.
• Contribute to continuous improvements in engineering processes, platform architecture, and production reliability.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related discipline, or equivalent practical experience.
• 3+ years of hands-on professional software engineering experience.
• Expert-level proficiency in at least one systems programming language, such as Go, C, or Rust.
• Strong understanding of data structures, algorithms, distributed software architecture, and systems engineering principles.
• Hands-on experience with Kubernetes, container orchestration, and container technologies.
• Experience automating software delivery and infrastructure workflows using continuous integration and deployment frameworks such as GitLab and ArgoCD.
• Strong scripting skills in Bash, Python, or a comparable scripting language.
• Solid understanding of Linux or other Unix-like operating systems and familiarity with system and kernel internals.
• Strong understanding of performance, security, reliability, and scalability considerations in complex distributed systems.
• Ability to work effectively in a distributed engineering environment with shifting priorities and technically complex challenges.
• Strong analytical and problem-solving skills, with the ability to investigate issues and translate technical findings into practical solutions.
• Clear technical communication skills and an interest in contributing to open-source projects.
• Experience with publish-subscribe architectures and message queues is an advantage.
• Experience optimizing high-throughput network paths and familiarity with unary, streaming, and bidirectional communication over HTTP/2 and gRPC is preferred.
• Experience developing Kubernetes Custom Resources and Operators for deployment in cloud service provider environments is a plus.

Benefits:

• Competitive salary aligned with experience, skills, and the local market.
• Generous benefits package designed to support employees' professional and personal needs.
• Opportunity to work on advanced AI infrastructure and distributed GPU computing technologies.
• Exposure to large-scale cloud-native systems, Kubernetes, systems programming, and high-performance computing.
• Opportunity to contribute to open-source software and collaborate with a global technical community.
• Work alongside experienced engineers on complex infrastructure and performance challenges.
• Distributed and collaborative work environment with opportunities for continuous technical learning and growth.
• Exposure to emerging AI, GPU, DPU, and cloud technologies.
• Opportunities to contribute to projects with broad impact across AI and accelerated computing.