Backend Engineer (6+ years of experience Job Vancouver BC Canada,Software Development

Position: Backend Engineer (6+ years of experience)

The Opportunity

At Nutanix, we're simplifying the future of AI with the Nutanix Cloud Platform for AI, enabling organizations to easily build, fine-tune, and run Generative AI, Large Language Models (LLMs), and next-generation Agentic AI applications without the complexity of managing AI infrastructure themselves. Our high-performance, full-stack machine learning cloud platform delivers AI-ready capabilities out of the box ("GPT-in-a-Box") through a software-defined, full-stack infrastructure solution that simplifies AI deployment across on-premises data centers, edge locations, and public clouds.

The Enterprise AI team is at the forefront of this innovation, driving strategic products such as LLM Inference, the AI Gateway, and the Agentic AI Platform, recently showcased at NVIDIA GTC and NEXT 2026. Join the team responsible for the foundational AI technologies powering the next wave of intelligent applications at Nutanix.

About the Team:
We are a fast-paced, globally distributed team building the foundational layers of the enterprise AI stack. By joining our team, you'll help shape the next generation of enterprise AI platforms, working at the intersection of large-scale distributed systems and machine learning infrastructure. This is an opportunity to solve complex technical challenges, influence the direction of key AI technologies, and build systems that power AI workloads at enterprise scale.

You will report to a seasoned Technical Lead/Manager who will provide mentorship and guidance as you navigate through your responsibilities. The work setup at Nutanix AI is a hybrid model, offering a blend of in-office collaboration and remote work flexibility. As a new hire, you will be expected to be in the office for 3 days a week, ensuring that you have the opportunity to engage with your team and foster strong working relationships.

Your Role

Architect, design, and develop horizontally scalable, containerized, fault-tolerant services on Kubernetes for enterprise AI and LLM workloads.

Build and operate high-performance inference and platform services that deliver low-latency, high-throughput experiences for Generative AI and Agentic AI applications.

Design and optimize critical system components across the stack, including distributed systems, storage, networking, and low-level infrastructure layers.

Develop and enhance multi-tenant platform services supporting on-premises, hybrid, and cloud-based AI deployments.

Design and implement scalable observability architectures using technologies such as Prometheus, Grafana, Datadog, Open Telemetry, and related cloud-native monitoring frameworks.

Debug complex production issues, perform root-cause analysis, and improve reliability, resiliency, and operational efficiency of platform services.

Build and maintain CI/CD pipelines and deployment automation to accelerate delivery of production-grade services.

Design and implement foundational LLM serving capabilities including request routing, rate limiting, token streaming, load balancing, quota management, and usage budgeting.

Collaborate closely with globally distributed product management, AI, and software engineering teams to deliver high-quality products in a fast-paced environment.

Contribute to all stages of the product lifecycle, including architecture, design, development, testing, experimentation, performance analysis, deployment, and operations.

Leverage and contribute to relevant open-source cloud-native and AI ecosystem projects.

Review code and design documents, provide feedback on product requirements, and champion engineering excellence across the team.

Continuously evaluate emerging technologies and help shape the technical direction of Nutanix's Enterprise AI Platform.

What You Will Bring

Required Qualifications

6+ years of experience developing maintainable, modular, resilient, fail-safe, and long-lived software products within a product development organization.

Strong computer science fundamentals including data structures, algorithms, operating systems, networking, and distributed systems.

Hands-on experience with Docker, Kubernetes, and cloud-native architectures.

Production experience developing backend systems using Go, Python, C++, or Rust.

Experience building, owning, and maintaining CI/CD pipelines and release automation end-to-end.

Strong understanding of datacenter architecture including compute, storage, networking, and virtualization.

Experience designing and deploying software across on-premises, cloud, and hybrid environments.

Demonstrated experience designing and tuning high-performance, performance-sensitive system software.

Solid understanding of distributed computing, distributed data stores, and large-scale service architectures.

Experience diagnosing and resolving production performance issues using observability and monitoring platforms such as Prometheus, Grafana, Datadog, Open Telemetry, or similar tools.

Familiarity with LLM serving concepts including rate limiting, token streaming, request scheduling, load…