The Opportunity
At Nutanix, we are expanding the capabilities of the Nutanix Kubernetes Platform (NKP) to power the next generation of enterprise AI. This platform will serve as the foundation for AI/ML workloads, GPU infrastructure, and enterprise applications, delivering hyperscaler-like capabilities in on-prem and hybrid deployments.As an Engineer on the NKP AI Platform team, you will be a key technical leader responsible for architecting, building, and scaling the infrastructure that allows enterprises to train, deploy, and manage mission-critical modern and AI Applications effortlessly.
About the Role
This is a high-impact, hands-on engineering role. You will bridge the gap between underlying container orchestration and advanced AI/ML workloads. You will be tackling hard problems in large-scale distributed systems, evolving toward global control planes, GPU scheduling, ensuring our platform is resilient, secure, and highly performant. Drive the design of and cell-based architectures
About the Team
NKP is a complete, enterprise-grade, production-ready platform based on Kubernetes that serves modern applications. By taking the best of the Cloud Native Computing Foundation (CNCF) ecosystem, but providing it in an integrated and lifecycle-managed package, NKP delivers all the functionality necessary in production with a dramatically lowered TCO. NKP provides simplified Kubernetes operations, seamless application mobility, and integrated security and compliance.
Platform engineers and IT admins can use NKP to keep all cloud native resources up-to-date with upgrades, patching, maintenance, and security. The technology and community in this industry are growing fast, new applications and solutions are coming to the market every day, new standards are becoming mature at full speed.
You will report to the Senior Engineering Manager, who adopts a collaborative leadership style that encourages team involvement in decision-making and values open discussions. The manager emphasizes the importance of strong communication and problem-solving skills, aiming to build a supportive environment for both personal and professional development.
This role does not require any travel, allowing the new hire to focus on their responsibilities within the local team while also collaborating effectively with their US counterparts through virtual meetings and communication tools.
What You Will Do (Responsibilities):
Develop Kubernetes Custom Resource Definitions (CRDs), Operators, and Controllers in Golang to natively orchestrate AI workloads.
Build scheduling intelligence for AI-native infrastructure, including GPU-aware scheduling, resource isolation, and workload orchestration
Seamlessly integrate and manage the lifecycle of leading open-source AI tools like Kubeflow, KServe, Ray, vLLM, and Triton Inference Server within the NKP stack.
Act as a force multiplier for the team. Drive architectural reviews, establish coding standards, and mentor junior and mid-level engineers.
Partner closely with Product Managers, the core NKP k8s, and Nutanix Data Services (NDK) to ensure seamless data gravity and persistent storage for AI workloads.
What You Will Bring (Requirements):
6-8 years of software engineering experience, with at least 3+ years focused on building scalable distributed systems, cloud platforms, or AI/ML infrastructure.
Language Proficiency:
Deep expertise in Golang (for K8s ecosystem) and Python (for ML ecosystem).
Extensive experience with Kubernetes internals, building K8s Operators, Controllers, and working with the Cluster API (CAPI).
Hands-on experience with MLOps frameworks and distributed AI computing (., Kubeflow, Ray, KServe, PyTorch DDP).
Strong understanding of Linux internals, networking, and container runtimes (containerd, Docker).
Proven track record of designing intuitive, developer-friendly APIs and scalable microservices architectures.
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field (or equivalent practical experience).
Nice to Haves:
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