AI Senior Staff Systems Engineer

Cadence Design Systems; San Jose (CA); On-site; USD 137,000 - 254,000; Full time

Job summary

Cadence Design Systems in San Jose seeks a Senior AI Systems Engineer to own the AI infrastructure lifecycle, from architecting GPU clusters to deploying advanced models.

The role combines hands-on GPU cluster management, LLM deployment, and production-grade agentic workflows, with emphasis on Docker, Kubernetes, PyTorch, TensorFlow, and CI/CD.

You will collaborate across on-prem and cloud (Azure OpenAI, GCP) and mentor engineers while ensuring security and performance.

Qualifications

• 10+ years in a senior technical role, with at least 5 years focused on building and operating high-performance computing or AI infrastructure.
• Expert-level knowledge of NVIDIA GPU architecture and technologies like CUDA and cuDNN.
• Proven experience with public cloud AI services, specifically Azure OpenAI and Google Cloud Platform (GCP).
• Extensive hands-on experience with Docker: image management, container orchestration, and troubleshooting.

Responsibilities

• AI Infrastructure Architecture & Strategy: Lead the design and implementation of next-gen AI infrastructure for Agentic AI initiatives.
• Cloud AI Service Integration: Manage access, usage, and billing for Azure OpenAI and GCP services.
• Hands-on GPU Cluster Management: Configure, install, and optimize GPU server clusters, troubleshoot hardware/software, tune performance.
• Full-Stack AI Tech Stack Development & Operations: Deploy and maintain PyTorch, TensorFlow, Docker, Kubernetes, and CI/CD pipelines.
• Advanced LLM Deployment & Optimization: Deploy and optimize LLMs using vLLM, TGI, TensorRT-LLM for high throughput and low latency.
• Agentic AI Workflow & Service Engineering: Build production-grade AI workflows integrating LLMs with tools, APIs, and databases; mentor engineers.
• Automation & Monitoring: Create automation scripts (Python/Bash/Perl); monitor system health, GPU utilization, container performance.
• AI Systems Support & Mentorship: Provide escalation engineering support and technical leadership on AI systems engineering and performance tuning.
• Security and Compliance: Implement security best practices for AI systems and data.

Skills

NVIDIA GPU architecture

CUDA

cuDNN

Azure OpenAI

GCP

Docker

Kubernetes

Python

Bash

Linux system administration

Tools

LSF

Docker

Kubernetes

CI/CD

Job description

## AI Senior Staff Systems EngineerApply: SAN JOSE: Full time: Posted Today: R51191## **At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.**We are seeking a highly skilled and experienced**AI Systems Engineer** to join our team. This is a hands-on, senior individual contributor role that will be pivotal in leading the development, operations, and support of our entire AI infrastructure. You will be responsible for the entire lifecycle of our AI systems, from architecting and building high-performance GPU clusters to deploying and optimizing our most advanced AI models and agentic services.Responsibilities * **AI Infrastructure Architecture & Strategy:** Lead the design and implementation of our next-generation AI infrastructure to support our Agentic AI initiatives. You will define the technical strategy for our on-premise GPU clusters, storage solutions, and networking to ensure optimal performance, scalability, and reliability for all our AI workloads.* **Cloud AI Service Integration:** Support and secure the use of public cloud AI services, including **Azure OpenAI services** and **Google Cloud Platform (GCP)** services like **Gemini**. This includes managing secure access, monitoring usage, and tracking billing to ensure cost-effectiveness. You will also have hands-on experience supporting compute, GPUs, and AI services on both GCP and Azure.* **Hands-on GPU Cluster Management:** Take a leadership role in the configuration, installation, and optimization of GPU server clusters. This includes advanced troubleshooting of hardware and software, performance tuning, and implementing best practices for cluster utilization and resource management. You will be an expert in administering job schedulers like **LSF** in a production environment, including integration with **Docker** for containerized job submission.* **Full-Stack AI Tech Stack Development & Operations:** Architect and deploy a robust and scalable AI tech stack. You will be responsible for the end-to-end operational lifecycle, including setting up and managing deep learning frameworks (**PyTorch**, **TensorFlow**), containerization with **Docker** and **Kubernetes**, and implementing CI/CD pipelines for AI model development.* **Advanced LLM Deployment & Optimization:** Lead the deployment, serving, and optimization of Large Language Models (LLMs). You will be an expert in techniques such as model quantization, distillation, and using high-performance serving frameworks (e.g., **vLLM**, **TGI**, **TensorRT-LLM**) to maximize inference throughput and minimize latency.* **Agentic AI Workflow & Service Engineering:** Architect and build production-grade Agentic AI workflows and services. You will be responsible for the technical design and implementation of systems that integrate LLMs with external tools, APIs, and databases, and will mentor other engineers on building robust and scalable AI agent applications.* **Automation & Monitoring:** Develop and maintain automation scripts using languages like **Python**, **Bash**, or **Perl**to streamline system maintenance, deployment, and reporting. Implement and manage monitoring solutions for system health, job statuses, GPU utilization, and container performance to proactively identify and resolve issues.* **AI Systems Support & Mentorship:** Act as the final escalation point for the most complex technical issues related to our AI infrastructure. You will also serve as a technical leader and mentor to other engineers, providing guidance on best practices in AI systems engineering, performance tuning, and operational excellence.* **Security and Compliance:** Develop and implement security best practices for our AI systems and data, ensuring compliance with relevant regulations and protecting our intellectual property.Required Skills and Qualifications * 10+ years of experience in a senior technical role, with at least 5 years focused on building and operating high-performance computing or AI infrastructure. Proven track record as a Principal or Senior Staff Engineer.* Expert-level knowledge of **NVIDIA GPU architecture** and technologies like **CUDA** and **cuDNN**. Extensive experience with multi-GPU and multi-node training and inference.* Proven experience with public cloud AI services, specifically managing access, usage, and billing for **Azure OpenAI** and **Google Cloud Platform (GCP)** services.* Extensive hands-on experience with **Docker**: image management, container orchestration, and troubleshooting.* Proficiency in scripting languages such as **Python**, **Bash**, or **Perl**.* Deep expertise in **Linux system administration** (**RHEL** preferred), including networking, storage, and performance tuning.* Familiarity with user authentication and integration using systems like **LDAP** or **Active Directory**.* Strong problem-solving and communication skills with the ability to work in a multi-platform, cross-functional, and geographically distributed team.Preferred/Bonus Skills * Understanding of AI job profiling and tuning (memory, GPU, I/O).* Experience administering **LSF** clusters in a production or research environment. Familiarity with other job schedulers like **Slurm** is a plus.* Experience with **LSF Docker integration** and job submission using container images.* Experience with **macOS/AppleSilicon** system admin tasks and troubleshooting.*The annual salary range for California is $136,500 to $253,500. You may also be eligible to receive incentive compensation: bonus, equity, and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the salary range is a guideline and compensation may vary based on factors such as qualifications, skill level, competencies and work location. Our benefits programs include: paid vacation and paid holidays, 401(k) plan with employer match, employee stock purchase plan, a variety of medical, dental and vision plan options, and more.*