Lead AI/ML Engineer – Security AI & LLMs
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About the Role
SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter, LinkedIn, Facebook and Instagram.
Role Overview
As our lead AI/ML Engineer, you will design, build, and scale the intelligence layer powering our next-generation security products. You will turn complex datasets—including configurations, security alerts, and raw network logs—into production-ready AI capabilities that drive automated analysis, reasoning, and intelligent recommendations.
Key Responsibilities
- Architect AI Systems: Design and deploy robust Retrieval-Augmented Generation (RAG) pipelines, agentic workflows, and LLM applications tailored to parse and reason over security telemetry and unstructured logs.
- Model Development & Tuning: Train, fine-tune, and evaluate ML/DL models for pattern matching, anomaly detection, and classification across massive, heterogeneous security datasets.
- Ensure AI Trust & Alignment: Implement strict guardrails, evaluation frameworks, and safety alignment techniques to ensure all model outputs and recommendations are deterministic, safe, and highly accurate.
- Establish MLOps: Build and maintain scalable ML pipelines (from data preprocessing to model monitoring in production), collaborating closely with Data and Product Engineers to ensure low-latency, secure inferences.
Required Experience & Skills
- Experience: 6+ years of professional experience deploying machine learning models into production, with 1+ years focused on LLMs and generative AI. Experience in the cybersecurity domain is highly valued.
- AI/NLP Stack: Deep expertise in Python, PyTorch/TensorFlow, and framew
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