Principal Staff Engineer, AI Platform Research, Data Science

About the Role:

CrowdStrike is looking for a hands-on Staff Data Engineer with deep expertise in Large Language Models (LLMs), Agents and AI platforms to join our growing Data Science Platform Engineering Team. You will be a key technical leader, responsible for designing, building, and deploying cutting-edge data infrastructure that powers our next generation of AI-driven security products. Given the rapid evolution of AI tooling and development standards, we seek a technical leader to stay at the forefront of research, optimizing these systems while driving the platform advancements that accelerate our research teams. This role requires significant hands-on experience in LLM integration, agentic workflows, and agent harnessing to deliver high-impact, scalable solutions. You will champion by hands on executing engineering excellence, focusing on shipping fast, writing elegant, high-quality code, and actively mentoring and strengthening the team's technical knowledge and capabilities.

What You'll Do:

• Write code everyday. Architect, implement, and optimize data platforms and pipelines specifically designed to support LLMs, Neural Networks, Retrieval-Augmented Generation (RAG), and sophisticated AI agentic systems at Exabyte scale.
• Drive the adoption and deployment of agentic workflows and agent harnessing techniques to create autonomous, data-driven security features.
• Lead by example in hands coding highly scalable, fault-tolerant, and cost-effective data solutions, emphasizing rapid iteration and high-quality deployment.
• Write elegant, production-ready code with a focus on performance, maintainability, and testing rigor, ensuring the ability to ship fast without compromising quality.
• Provide technical leadership and deep expertise in data modeling, normalization, and semantic cataloging for AI/ML workloads.
• Establish best practices for MLOps/DataOps surrounding LLMs, including monitoring, observability, and zero-touch recovery mechanisms for AI services.
• Actively mentor engineers, conducting technical workshops, leading design reviews, and strengthening the team's knowledge in cutting-edge AI platform technologies.
• Collaborate across the organization with Data Scientists, Product Managers, and other engineering teams to transform research prototypes into robust, production-grade services.
• Own the end-to-end lifecycle of critical data services: development, testing, deployment, and monitoring.

Tech Stack:

• Languages: Expert-level proficiency in at least one — Python, Go, Rust, or JVM technologies.
• AI/ML: MLOps tools (MLflow, SageMaker, Vertex AI); agentic frameworks (LangChain, LlamaIndex).
• Distributed Processing: Spark, Dask, or Flink.
• Cloud: AWS, GCP, or OCI and related data services.
• Containers & Orchestration: Docker, Kubernetes.
• Streaming: Kafka, Pulsar.
• Data Warehousing & Orchestration: Snowflake, BigQuery, Airflow, Kubeflow.

What You'll Need:

• Bachelor’s, Master’s or PhD in Computer Science, Data Engineering, or a related STEM field, or equivalent practical experience.
• 5+ years of progressive experience in Data Engineering/Platform Engineering, with at least 3 years focused on architecting and building platforms for AI/ML or Data Science at massive scale.
• Demonstrable hands-on experience in LLM engineering (fine-tuning, prompt engineering, deployment), RAG, and developing agentic workflows.
• Proven track record of designing and delivering large-scale distributed systems (sharding, partitioning, concurrency).
• Exceptional ability to write clean, elegant, performant, and well-tested code, coupled with a proactive mindset for delivering results quickly.
• Ability to leverage AI aided secure code development
• A thorough understanding of engineering practices, including effective peer code reviews, resilient architecture design, and comprehensive testing paradigms.
• Prior experience in a Staff level engineering role, demonstrating 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.
• Contributions to open-source projects related to data or AI/ML.

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