CrowdStrike is an award-winning, global provider of cloud-delivered security technology, threat intelligence, and next-generation endpoint protection. Founded i
Senior AI Infrastructure Engineer, LLM/AI Platforms
Location
United States
Posted
3 days ago
Salary
$140K - $215K / year
Seniority
Senior
Job Description
Senior AI Infrastructure Engineer, LLM/AI Platforms
CrowdStrike
• Provision and configure large GPU clusters and compute resources for LLM training, finetuning, and inference workloads. • Develop and optimize LLM model-serving infrastructure, including deployment and optimization of various inference frameworks. • Lead model lifecycle management including versioning, checkpointing and reproducibility across training and inference deployments. • Design and champion robust evaluation frameworks to assess model performance, accuracy, and reliability, ensuring AI systems are consistently at production-ready standards. • Identify and address GPU utilization and GPU memory efficiency bottlenecks and apply techniques like quantization, batching, and caching. • Architect and maintain data platforms and pipelines specifically designed to support LLMs, Retrieval-Augmented Generation (RAG), and AI Agentic Systems at scale. • Deliver production-ready code with a focus on performance, maintainability, and testing rigor, ensuring the ability to ship fast without compromising quality. • Apply expertise in data modeling, normalization, and semantic cataloging for AI/ML workloads. • Define and enforce best practices for MLOps/DataOps surrounding LLMs, including monitoring, observability, and zero-touch recovery mechanisms for AI services. • Document architectural designs thoroughly and communicate technical decisions clearly to stakeholders. • Collaborate across the organization with Data Scientists, Product Managers, and other engineering teams to transform research prototypes into robust, production-grade services.
Job Requirements
- Bachelor’s degree in Computer Science, Data Engineering, or a related STEM field; Master’s degree preferred
- 6+ years of experience in Infrastructure/Data Engineering, with at least 2 years focused on building and maintaining platforms/pipelines that support LLM-based systems and applications
- Demonstrable hands-on experience in LLM infrastructure engineering including cluster provisioning, optimizing training workloads, and maintaining inference pipelines
- Exceptional ability to write clean, elegant, performant, and well-tested code, coupled with a strong focus on action and delivering results quickly
- Thorough understanding of engineering practices including effective peer code reviews and resilient architecture design
- Demonstrates technical leadership and mentorship capabilities
- Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.
Benefits
- Market leader in compensation and equity awards
- Comprehensive physical and mental wellness programs
- Competitive vacation and holidays for recharge
- Paid parental and adoption leaves
- Professional development opportunities for all employees regardless of level or role
- Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections
- Vibrant office culture with world class amenities
- Great Place to Work Certified™ across the globe
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