Rapid7 is looking for a Senior Software Engineer to drive the end-to-end delivery of advanced ML and LLM-based solutions for our security products. In this role, you will build and deploy production-grade agentic AI workflows and RAG pipelines on AWS to protect our customers from evolving cyber threats.

About the Team

The AI Center of Excellence is a multidisciplinary team of Data Scientists and AI Engineers who conduct research and build production-ready AI components to protect our customers' attack surfaces. We partner with Detection and Response teams to apply cutting-edge machine learning, LLMs, and agentic systems to solve real-world cybersecurity challenges at scale.

About the Role

As a Senior Software Engineer – Data Science, your primary responsibility will be to lead the design, development, and deployment of high-impact machine learning and generative AI solutions. Specifically, your focus will be to:

• Lead the end-to-end delivery of ML pipelines, including feature engineering and model training for malware detection and user behavioral analytics.

• Architect and maintain sophisticated LLM orchestration workflows using LangChain and LangGraph, incorporating RAG pipelines and vector databases.

• Manage production ML lifecycles on AWS (SageMaker, Bedrock, EKS) by implementing model versioning, drift detection, and automated retraining workflows.

• Drive technical excellence across the team by mentoring junior engineers, conducting code reviews, and establishing standards for model explainability and evaluation.

The skills and qualities you’ll bring include:

• Technical Ownership: A proactive approach to managing the full ML lifecycle from initial prototype to production monitoring.

• Collaborative Problem Solving: Ability to work across teams to translate complex security challenges into actionable AI/ML requirements.

• Continuous Learning: A commitment to staying current with evolving frameworks in NLP, agentic AI, and generative modeling.

• Python Expertise: Advanced proficiency in Python and the scientific computing stack (NumPy, Pandas, Scikit-learn).

• Deep Learning Proficiency: Hands-on experience with NLP workloads and behavioral modeling using PyTorch or TensorFlow.

• Generative AI Orchestration: Proven ability to build agentic workflows and RAG systems using LangChain, LangGraph, and vector databases.

• AWS Cloud Engineering: Strong experience deploying and scaling ML workloads via SageMaker, Bedrock, and Lambda.

• MLOps & CI/CD: Practical knowledge of building automated pipelines for model registry, testing, and deployment (GitHub Actions, Jenkins).

• LLM Evaluation & Governance: Experience using tools like Promptfoo or HELM to implement guardrails and evaluate model performance.

• Cybersecurity Domain Knowledge: Familiarity with threat detection, malware analysis, or security operations.

• Statistical Modeling: Strong understanding of supervised/unsupervised learning, anomaly detection, and explainability (SHAP, LIME).
   

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.