2 hours ago
Vancouver, CanadaStaff+
Responsibilities
- Architect, design, and develop scalable, containerized, fault-tolerant services for enterprise AI and LLM workloads.
- Build and operate high-performance inference and platform services with low latency and high throughput.
- Design distributed systems, storage, networking, and low-level infrastructure components across on-premises, hybrid, and cloud environments.
- Develop multi-tenant platform services and scalable observability architectures.
- Build and maintain CI/CD pipelines and deployment automation.
- Implement LLM-serving capabilities including request routing, token streaming, rate limiting, load balancing, quota management, and usage budgeting.
- Diagnose production issues, perform root-cause analysis, and improve platform reliability, resiliency, and operational efficiency.
- Contribute across architecture, design, development, testing, experimentation, performance analysis, deployment, and operations.
- Collaborate with product management, AI, and software engineering teams and contribute to code and design reviews.
- Evaluate emerging technologies and help shape the technical direction of the Enterprise AI Platform.
Requirements
- 6+ years of experience developing maintainable, modular, resilient, fail-safe, and long-lived software products.
- Strong fundamentals in data structures, algorithms, operating systems, networking, and distributed systems.
- Hands-on experience with Docker, Kubernetes, and cloud-native architectures.
- Production backend development experience with Go, Python, C++, or Rust.
- Experience owning CI/CD pipelines and release automation end to end.
- Strong understanding of datacenter compute, storage, networking, and virtualization.
- Experience deploying software across on-premises, cloud, and hybrid environments.
- Experience designing and tuning high-performance system software and diagnosing production performance issues with observability platforms.
- Familiarity with LLM serving concepts, reasoning workflows, tool calling, prompt templates, and agent systems.
- Experience building multi-tenant services on virtualized or containerized infrastructure.
- Master's degree in Computer Science or equivalent practical experience.
- Preferred experience with PyTorch, TensorFlow, GPU acceleration, vLLM, DeepSpeed, Hugging Face TGI, Triton, RAG, vector databases, AI orchestration frameworks, production AI platforms, LLM APIs, agentic systems, inference infrastructure, or open-source distributed codebases.
Benefits
- Hybrid work arrangement with a minimum of three onsite days per week in applicable locations.
- RRSP with dollar-for-dollar matching up to 7% of base salary.
- Mental health coverage and paramedical benefits.
- Fully paid maternity and parental leave and bereavement leave, including pet loss.
- RSUs and an Employee Stock Purchase Plan with a 15% discount.
Categories
About Nutanix
Nutanix is a global leader in cloud software, offering organizations a single platform for running apps and data across clouds. With Nutanix, companies can reduce complexity and simplify operations, freeing them to focus on their business outcomes. Building on its legacy as the pioneer of hyperconverged infrastructure, Nutanix is trusted by companies worldwide to power hybrid multicloud environments consistently, simply, and cost-effectively. Learn more at www.nutanix.com or follow us on social media @nutanix.