Principal Staff Engineer, AI Platform Research, Data Science

What you'll do

• Architect and optimize data platforms for LLMs, Neural Networks, RAG, and agentic systems at exabyte scale.
• Develop and deploy automated, data-driven security features using agentic workflows and harnessing techniques.
• Write high-quality, production-ready code focused on performance, maintainability, and rigorous testing.
• Provide technical leadership in data modeling, normalization, and semantic cataloging for AI/ML workloads.
• Establish MLOps and DataOps best practices including monitoring, observability, and zero-touch recovery.
• Mentor engineers through technical workshops, design reviews, and knowledge sharing on AI technologies.
• Transform research prototypes into robust, production-grade services in collaboration with cross-functional teams.
• Manage the end-to-end lifecycle of critical data services from development to monitoring.

What we're looking for

• 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.
• At least 3 years of experience architecting and building platforms for AI/ML or Data Science at massive scale.
• Demonstrable hands-on experience in LLM engineering, RAG, and developing agentic workflows.
• Proven track record of designing and delivering large-scale distributed systems including sharding, partitioning, and concurrency.
• Prior experience in a Staff level engineering role demonstrating technical leadership and mentorship capabilities.
• Expert-level proficiency in Python, Go, Rust, or JVM technologies.
• Experience in cybersecurity, intelligence, or high-compliance industries (preferred).