Principal Software Engineer – Nvidia AI Ecosystem

Responsibilities

• Architect and lead the implementation of new features and joined solutions for Red Hat AI & Cloud with Nvidia cutting edge technologies: GPU, DPU and more
• Explore deep code integration into various Red Hat products, ensuring optimal integration between the Red Hat portfolio, hardware accelerators and partners
• Provide technical vision and leadership on critical and high-impact projects, ensuring non-functional requirements including security, resiliency, and maintainability are met
• Collaborate closely with UX, UI, QE, and cross‑functional teams to deliver a great experience to Red Hat partners and customers
• Coordinate with team leads, architects, and other engineers on the design and architecture of our offerings
• Become responsible for the quality of our offerings, participate in peer code reviews and continuous integration (CI), and respond to security threats
• Mentor, influence, and coach a distributed team of engineers, contributing to a culture of continuous improvement by sharing recommendations and technical knowledge
• Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI capabilities into existing workflows and tooling

• 7+ years of relevant technical experience in software development
• Advanced experience working in a Linux environment with at least one language like Golang, Python, Java, C, or C++
• Advanced experience with a container orchestration ecosystem like Kubernetes, or Red Hat Open Shift
• Strong experience with microservices architectures and concepts including APIs, versioning, monitoring, etc.
• Virtual Networking / Software Defined Networking (SDN) experience
• Experience with AI/ML technologies, including foundational frameworks, large language models (LLMs) and orchestration tools
• Ability to quickly learn and guide others on using new tools and technologies
• Proven ability to innovate and a passion for staying at the forefront of technology
• Excellent system understanding and troubleshooting capabilities
• Autonomous work ethic, thriving in a dynamic, fast-paced environment
• Proficient written and verbal communication skills in English.
• The following is considered a plus:

• Experience with cloud development for public cloud services (AWS, GCE, Azure)
• Background in Dev Ops or site reliability engineering (SRE)
• Experience with hardware accelerators (e.g., GPUs, CUDA, DOCA) for AI workloads
• Recent hands‑on experience with distributed computation, either at the end‑user or infrastructure provider level
• Experience with performance analysis tools
• Experience with Linux kernel development

• Golang
• Python
• Java
• C
• C++
• Kubernetes
• Red Hat Open Shift
• microservices
• AI/ML technologies
• Linux kernel development

• technical vision
• leadership
• mentoring
• collaboration
• troubleshooting
• autonomous work ethiccommunication skills
• innovation
• continuous improvement
• adaptability