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Rapid7 is looking to expand its global AI footprint by developing and deploying production-ready AI models and systems to protect customer attack surfaces and strengthen cybersecurity defenses across their product suite.

Requirements

• Proven experience building and deploying AI systems in production using Python and modern ML frameworks
• Hands-on expertise with: scikit-learn, PyTorch, TensorFlow – for model development
• Hands-on expertise with: AWS Bedrock, Sagemaker, HuggingFace, or similar cloud AI stacks
• Hands-on expertise with: CrewAI or other orchestration frameworks for agentic AI systems
• Hands-on expertise with: Pandas, NumPy, Airflow, or Databricks for data engineering and workflow automation
• Strong understanding of model lifecycle management, including monitoring, retraining, and versioning
• Ability to balance trade-offs between model performance, latency, and interpretability

Responsibilities

• Design, prototype, and deliver production-ready AI models and systems
• Design, implement, and optimize AI models and systems across a range of cybersecurity use cases
• Balance hands-on technical work with cross-functional collaboration
• Work across both R&D and production environments, leveraging AWS (Bedrock, Sagemaker) and modern AI frameworks
• Ensure AI is seamlessly integrated into Rapid7’s products and services to deliver measurable customer value
• Contribute to best practices for model experimentation, evaluation, and observability
• Mentor team members on architecture, model design, and debugging

Other

• Lead the technical implementation of AI projects from prototyping through production deployment
• Collaborate closely with product managers, data scientists, and software engineers to align efforts with business goals
• Stay current on emerging AI methods, tools, and frameworks relevant to cybersecurity, sharing learnings across teams
• Familiarity with cybersecurity, or experience in other high-signal domains such as finance, healthcare, or marketplaces, is a strong plus
• Communicate complex technical concepts clearly to both technical and non-technical audiences