Lead the design and implementation of large-scale data architectures for cloud-based systems (AWS, Azure) to efficiently ingest, store, and process massive volumes of security telemetry and alerts
Spearhead advanced AI/ML initiatives, including Generative AI, to develop end-to-end AI solutions for SOC automation, threat detection, and threat hunting, leveraging frameworks like Scikit-learn, TensorFlow, and PyTorch
Drive the use of Large Language Models (LLMs) and AI Agents to enhance the enrichment of security data, enabling faster human decision-making, while exploring and evaluating various LLM architectures
Collaborate across teams to integrate ML-driven insights into the platform and apply automation and analytics to reduce analyst workload and enhance detection fidelity
Provide architectural guidance across engineering based on the fast-paced world of GenAI, Agents, and classic ML models, including those developed by our internal R&D teams

Requirements

12+ years of experience inclusive of data architecture and AI/ML, with a track record of designing and implementing large-scale data systems and production-grade ML solutions
Proficiency in Python (for data processing and ML pipelines), cloud platforms (AWS and/or Azure including data storage, compute services, and security controls), and MLOps best practices
Bachelor's degree in Computer Science or a related field or equivalent

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architectureAIMLGenerative AIPythonMLOpslarge-scale data systemsML solutionsdata processingML pipelines

Soft Skills

leadershipcollaborationcommunication