AI Engineer
Rapid7
Job Overview
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Job Description
About The Team
The AI Center of Excellence at Rapid7 leverages advanced machine learning, Large Language Models (LLMs), and agentic systems to enhance threat detection and automate security workflows for our global customers. We transform over 20 years of threat intelligence into proactive defense features through a collaborative, research-driven engineering environment.
About The Role
As an AI Engineer, your primary responsibility will be to contribute to the end-to-end development, evaluation, and monitoring of ML and LLM-based security features. Your tasks will include:
- Execute data acquisition, cleaning, and feature engineering to prepare high-quality datasets for security modeling.
- Build and evaluate supervised and unsupervised ML models, including classification, clustering, and anomaly detection.
- Develop and optimize LLM-based workflows, including prompt engineering and the implementation of Retrieval-Augmented Generation (RAG) pipelines.
- Support the deployment and observability of models on AWS infrastructure using established CI/CD pipelines.
The Skills And Qualities You’ll Bring Include
- A courageous and curious mindset, demonstrating a strong ability to learn new technologies and operate in ambiguous problem spaces.
- Exceptional collaboration skills with the ability to work cross-functionally with senior scientists and engineers to ship production features.
- Strong ownership and principled decision-making when evaluating model performance and data quality.
- 2–5 years of professional experience in Data Science or ML Engineering roles.
- Proficiency in Python and its scientific ecosystem, specifically Pandas, NumPy, and scikit-learn.
- Hands-on experience building and tuning supervised and unsupervised machine learning models.
- Working knowledge of AWS ML services, including SageMaker, S3, Bedrock, and Lambda.
- Foundational exposure to LLM orchestration frameworks such as LangChain or HuggingFace Transformers.
- Understanding of deep learning frameworks (PyTorch or TensorFlow) for NLP or sequence-based problems.
- Familiarity with model evaluation metrics and explainability techniques like SHAP or LIME.
- Basic understanding of CI/CD pipelines (GitHub Actions/Jenkins) and version control for ML workloads.
- Experience monitoring model performance and drift using tools like CloudWatch.
We know that the best ideas and solutions come from multi-dimensional teams. That’s because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don’t be shy - apply today.
About Rapid7
At Rapid7, our vision is to create a secure digital world for our customers, our industry, and our communities. We do this by harnessing our collective expertise and passion to challenge what’s possible and drive extraordinary impact. We’re building a dynamic and collaborative workplace where new ideas are welcome.
Protecting 11,000+ customers against bad actors and threats means we’re continuing to push the envelope just like we’ve been doing for the past 20 years. If you’re ready to solve some of the toughest challenges in cybersecurity, we’re ready to help you take command of your career. Join us.
Key skills/competency
- Machine Learning
- Large Language Models (LLMs)
- Data Science
- Python
- AWS
- Threat Detection
- Prompt Engineering
- RAG Pipelines
- MLOps
- Security Analytics
How to Get Hired at Rapid7
- Research Rapid7's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Customize your resume and cover letter to highlight experience in ML, LLMs, and cybersecurity relevant to Rapid7.
- Showcase technical prowess: Prepare to discuss your Python, AWS, and ML/LLM project experience with Rapid7's engineers.
- Understand cybersecurity challenges: Familiarize yourself with current threat detection and security automation trends relevant to Rapid7.
- Practice behavioral questions: Be ready to demonstrate collaboration, ownership, and problem-solving skills for Rapid7.
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