Senior AI Engineer

DLP's rule-based framework is broken. We asked machines to find problems with rigid rules, then expected humans to investigate the noise - an impossible task. Jazz is the new model. It starts with total coverage from a forensic endpoint agent and uses a powerful Agentic Investigator that learns your business. It delivers clear, pre-investigated answers instead of alerts, and is designed to be run by a single person. Finally, DLP that works.

We are seeking a Senior AI Engineer to build the intelligence layer for Jazz. In this role, you will solve core product challenges involving large language models and highly imbalanced security datasets. You will design and implement generative workflows and agent-based AI systems that operate reliably at production scale.

What You’ll Do

• Drive the integration and production deployment of cutting-edge AI frameworks directly into our core product, unlocking the power of scalable, AI-powered applications that redefine our capabilities.
• Design and implement generative workflows including agentic systems, tool-using LLMs, retrieval pipelines (RAG), and vector search infrastructure.
• Build and deploy models for classification, generation, and embeddings tailored to real-world security use cases.
• Develop automated testing, evaluation, and monitoring systems to ensure model performance and data quality in production environments.
• Work across the full model lifecycle from experimentation and development to deployment, optimization, and maintenance.
• Collaborate closely with product and engineering teams to integrate AI capabilities into the platform.
• Contribute to high engineering standards and provide technical mentorship within the team.
  
  

• 4–6+ years of experience in machine learning engineering or applied AI, with a preference for an MSc or PhD in a relevant field.
• Hands-on experience building and deploying large-scale production systems with machine learning components.
• Practical experience with modern AI architectures, including LLMs, RAG pipelines, vector search, and prompt orchestration.
• Strong backend engineering experience and familiarity with building production services.
• Experience implementing and productionizing AI frameworks with automated testing, monitoring, and data quality controls.
• Strong architectural thinking and algorithmic intuition for model selection, evaluation, and optimization.
• Ability to work independently in fast-moving environments and take ownership of complex technical challenges.
  
  

• Work on complex problems at the intersection of AI, cybersecurity, and large-scale systems.
• Build production AI systems that power a new approach to Data Loss Prevention.
• Take ownership in an early-stage company where engineering decisions shape the product.
• Collaborate with a team focused on solving hard technical challenges with high standards of engineering.