About the Team
The AI Center of Excellence is a multidisciplinary group of Data Scientists and AI Engineers who partner with Detection and Response teams to turn cutting-edge research into real-world security products. We leverage LLMs, agentic workflows, and behavioral modeling to stay ahead of evolving threats and ensure our customers remain secure.
About the Role
As a Senior Software Engineer – Data Science, your primary responsibility will be to drive the end-to-end delivery of ML and LLM-based solutions on AWS.
Specifically, your focus will be to:
Design and implement sophisticated ML pipelines for security use cases, including malware detection and user behavioral analytics.
Architect and maintain RAG pipelines and agentic AI workflows using toolchains like LangChain and LangGraph to automate complex security tasks.
Optimize and deploy models within the AWS ecosystem, utilizing SageMaker and Bedrock while ensuring robust monitoring, drift detection, and retraining workflows.
Collaborate and mentor across the team to establish architectural standards, conduct code reviews, and support the technical growth of junior engineers.
The skills and qualities you’ll bring include:
Core Skills
Technical Ownership: Ability to take a project from a conceptual prototype to a high-quality production system.
Analytical Problem Solving: Expertise in applying scientific computing and statistical modeling to unlabeled, large-scale data.
Continuous Learning: A proactive approach to mastering emerging technologies in LLMs, Generative AI, and agentic systems.
Functional Skills
Python Proficiency: Advanced experience with numpy, pandas, and scientific computing libraries.
Machine Learning Frameworks
:
Hands-on expertise with scikit-learn and Deep Learning frameworks (PyTorch or TensorFlow).
Generative AI Toolchains: Proven experience with HuggingFace, Transformers, LangChain, and LangGraph.
Cloud Infrastructure: Strong experience deploying and operating ML workloads on AWS (SageMaker, Bedrock, Lambda, EKS).
Vector Databases & RAG: Practical experience designing and tuning Retrieval-Augmented Generation pipelines.
MLOps & CI/CD: Proficiency in managing model registries, versioning, and automated deployment via GitHub Actions or Jenkins.
Security Domain Knowledge: Familiarity with threat detection, malware behaviour, or cybersecurity analytics.
Model Explainability: Ability to implement and interpret model transparency tools like SHAP or LIME.
LLM Evaluation: Experience using evaluation frameworks such as Promptfoo or HELM to ensure model quality and safety.
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.
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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.
