Sr. AI Infrastructure Engineer, LLM/AI Platforms (Remote)
CrowdStrike · USA - Remote ·
- Work mode
- Remote
- Seniority
- Senior
- Category
- AI engineering
- Experience
- 2+ years
- Visa sponsorship
- Yes
- Company size
- 1000+
- Salary
- USD 140,000 – 215,000 / year
CrowdStrike · USA - Remote ·
Build and scale the AI infrastructure that powers CrowdStrike’s LLM-driven security products, including GPU clusters, model-serving pipelines, and MLOps tooling.
As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.
About the Role:
CrowdStrike is looking for a Senior AI Infrastructure Engineer with expertise in Large Language Models (LLMs) Infrastructure and data platforms to join our growing AI Infrastructure Team. You will be a key leader, helping to design, build, and deploy cutting-edge AI infrastructure that powers our next generation of AI-driven security products. This role requires hands-on experience in LLM infrastructure to support multiple large scale training pipelines and scalable AI-powered systems. You will champion engineering best practices, write high-quality code, and actively mentor and strengthen the team’s technical knowledge and capabilities.
CrowdStrike is a computer security company, but we do not require candidates for this role to have prior security industry experience. We will mentor and train in security topics as needed. We do expect a strong interest in CrowdStrike's mission and a willingness to engage with the needs of our product teams.
The scale of our systems and data are approaching Exabytes in size. Experience with extremely large-scale systems, including DevSecOps patterns, practices, and standards are important for this work.
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.
Hands-on experience with MLOps Tools (MLflow, Sagemaker, Vertex AI).
Strong understanding of CUDA, NVIDIA drivers, GPU, and TPU compute fundamentals.
Experience with inference serving frameworks such as vLLM and Triton Inference Server.
Proficiency with distributed training frameworks including Pytorch, Ray, Megatron, and JAX.
Expert-level proficiency in a high-level coding language (Python).
Deep knowledge of containerization and orchestration (Docker, Kubernetes, Slurm, Airflow).
Proficiency with Infrastructure as Code tooling like Terraform and Ansible.
Experience with cloud platforms (AWS, GCP, or OCI) and related data services.
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.
Bonus Points:
Prior experience in the cybersecurity, intelligence, or high-compliance industries.
Direct experience building, deploying, and managing LLMs in a production environment.
Experience with common agentic workflow frameworks (e.g., LangChain, LlamaIndex).
Experience with distributed data processing frameworks (e.g., Spark, Dask, Flink).
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Benefits of Working at CrowdStrike:
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
CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.
CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements.
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Right to Work
CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 - $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off.For detailed information about the U.S. benefits package, please click here.
Expected Close Date of Job Posting is:09-06-2026