Data Engineer (Remote)

Job summary

Architect and operate exabyte-scale data platforms and pipelines for LLMs, RAG, and autonomous AI agents, including production deployment, monitoring, and recovery. Lead adoption of agentic workflows and MLOps/DataOps practices, mentor engineers, and collaborate across teams to turn research prototypes into reliable security services.

Job details

About The Company CrowdStrike is a global leader in cybersecurity, dedicated to protecting organizations by leveraging innovative AI-native platforms and advanced security solutions. Since its inception in 2011, the company has been committed to stopping breaches and redefining modern security through cutting-edge technology. CrowdStrike processes nearly 3 trillion events daily across large-scale distributed systems, serving clients across various industries worldwide. The company's mission-driven culture emphasizes responsible AI adoption, continuous experimentation, and innovation. CrowdStrike fosters a flexible working environment that promotes autonomy, career growth, and a shared commitment to safeguarding digital assets. As a pioneer in AI-powered cybersecurity, CrowdStrike continually strives to deliver scalable, high-impact solutions that keep businesses, communities, and individuals safe. About The Role We are seeking a highly skilled Principal Data Engineer with specialized expertise in Large Language Models (LLMs) and AI platforms to join our expanding Data Science Platform Engineering team. In this pivotal role, you will lead the design, development, and deployment of advanced data infrastructure that underpins our next-generation AI-driven security products. Your responsibilities include integrating LLMs, developing agentic workflows, and harnessing AI agents to create autonomous, scalable security solutions. The ideal candidate will demonstrate a strong commitment to engineering excellence by delivering high-quality, performant code and mentoring team members to elevate overall technical capabilities. This role requires deep experience with large-scale systems, including DevSecOps practices, to handle data volumes approaching exabytes. Collaboration with cross-functional teams such as Data Scientists, Product Managers, and other engineering groups will be essential to transform innovative research into reliable, production-ready services. Qualifications Master’s degree or PhD in Computer Science, Data Engineering, or a related STEM field, or equivalent practical experience. 10+ years of progressive experience in Data Engineering or Platform Engineering, with at least 3 years focused on AI/ML platform development at large scale. Hands-on experience with Large Language Models (fine-tuning, prompt engineering, deployment) and Retrieval-Augmented Generation (RAG). Proven expertise in designing and implementing large-scale distributed systems, including sharding, partitioning, and concurrency management. Proficiency in high-level programming languages such as Python or JVM technologies. Deep understanding of distributed data processing frameworks like Spark, Dask, or Flink. Strong experience with cloud platforms such as AWS, GCP, or OCI, and related data services. Expertise in containerization and orchestration tools like Docker and Kubernetes. Knowledge of message queuing and streaming technologies such as Kafka or Pulsar. Experience with Data Warehousing solutions (Snowflake, BigQuery) and Data Orchestration tools (Airflow, Kubeflow). Demonstrated leadership in technical mentorship, design reviews, and cross-team collaboration. Responsibilities Architect, develop, and optimize data platforms and pipelines tailored for LLMs, RAG, and autonomous AI agentic systems at exabyte scale. Lead the deployment and adoption of agentic workflows and harnessing techniques to develop autonomous, data-driven security features. Design scalable, fault-tolerant, and cost-efficient data solutions emphasizing rapid iteration and high-quality deployment. Write clean, performant, and well-tested production code, maintaining a focus on performance and maintainability. Establish best practices for MLOps and DataOps, including monitoring, observability, and zero-touch recovery mechanisms for AI services. Mentor engineers through technical workshops, design reviews, and knowledge sharing to strengthen team capabilities in AI platform technologies. Collaborate with Data Scientists, Product Managers, and engineering teams to convert research prototypes into robust production services. Own the entire lifecycle of critical data services from development through deployment and ongoing monitoring. Benefits Competitive salary with market-leading compensation and equity awards. Comprehensive physical and mental wellness programs. Generous vacation policies and paid holidays to support work-life balance. Paid parental and adoption leave benefits. Opportunities for professional development and continuous learning. Participation in employee networks, volunteer programs, and community building activities. Access to a vibrant office culture with world-class amenities where applicable. Recognition as a Great Place to Work™ globally. Equal Opportunity CrowdStrike is an equal opportunity employer committed to fostering an inclusive environment where all employees and applicants are valued and respected. We do not discriminate based on race, color, religion, gender, sexual orientation, gender identity, marital status, veteran status, age, national origin, disability, or any other protected characteristic under law. We support veterans and individuals with disabilities through our affirmative action programs and strive to create a workplace that reflects diversity and promotes equal opportunity for all. We are dedicated to ensuring fair employment practices and providing accommodations to qualified individuals throughout the hiring process.

What you’ll do

Architect and operate exabyte-scale data platforms and pipelines for LLMs, RAG, and autonomous AI agents, including production deployment, monitoring, and recovery. Lead adoption of agentic workflows and MLOps/DataOps practices, mentor engineers, and collaborate across teams to turn research prototypes into reliable security services.

Requirements

Requires a master’s degree or PhD in a relevant STEM field, or equivalent practical experience, and 10+ years in data or platform engineering, including at least 3 years developing large-scale AI/ML platforms. Candidates should have hands-on LLM and RAG experience, expertise in distributed data systems and processing, cloud and container technologies, streaming, warehousing, orchestration, and technical leadership.

Benefits

• Competitive Salary
• Equity Awards
• Physical And Mental Wellness Programs
• Generous Vacation Policies
• Paid Holidays
• Paid Parental And Adoption Leave
• Professional Development
• Employee Networks
• Volunteer Programs

Listed skills

• Kubernetes · Preferred
• Docker · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Engineering
• AI/ML Platform Development
• Large Language Models
• Retrieval-Augmented Generation
• Distributed Systems
• Python
• JVM Technologies
• Spark
• Dask
• Flink
• Cloud Platforms
• Docker
• Kubernetes
• Kafka
• Data Warehousing
• Data Orchestration

Job areas

• Technology
• Data & Analytics
• Software
• Engineering
• Security & Safety

More jobs from Wiraa