In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. Youll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions.
This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform.
What Youll Do:
Own End-to-End Model Development (Research → Production)
Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization.
Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks.
Ensure models are robust, explainable, and production-ready in real-world enterprise environments.
Partner Deeply with Product & Engineering
Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives.
Work hands-on with engineering to integrate models into production systems and data pipelines.
Balance research depth with pragmatic execution and business impact.
Build AI Security Intelligence
Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability.
Work with structured and unstructured data, including logs, prompts, model outputs, and metadata.
Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors.
Lead Research POCs & Innovation
Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product.
5+ years of experience in Data Science or Applied ML roles.
3+ years of backend development experience, working with production systems.
Strong hands-on experience with language models / LLMs and modern ML techniques.
Bachelors degree in Computer Science (or equivalent practical experience).
Proven experience owning end-to-end research POCs, from ideation to real-world impact.
Strong understanding of product and business value, with a bias toward lean, effective solutions.
Deep understanding of language models
