Senior AI Engineer (Data Science)
Experience: 5–8 years

About the Team
The AI Center of Excellence team includes Data Scientists and AI Engineers that work together to conduct research, build prototypes, design features, and build production AI components and systems. Our mission is to leverage the best available technology to protect our customers' attack surfaces.

We partner closely with Detection and Response teams, including our MDR service, to apply AI/ML to real-world security challenges. The team values strong technical ownership, high-quality execution, and continuous learning across ML, LLMs, and agentic AI systems.

The technologies we use include:
 • Python for analysis and modelling using numpy, pandas, and scientific computing libraries

 • Jupyter notebooks (local & remote)

 • scikit-learn for machine learning

 • Anomaly detection for large-scale unlabeled data analysis

 • Deep learning frameworks for NLP and behavioural modelling

 • LLM/GenAI toolchains: HuggingFace, Transformers, LangChain, LangGraph

 • RAG pipelines using vector databases

 • AWS cloud ecosystem: SageMaker, Bedrock, Lambda, EKS, S3

 • CI/CD for ML/LLM (GitHub Actions, Jenkins)

 • Monitoring and observability (CloudWatch, Prometheus, Grafana)

 • The role at Rapid7 is for a Senior Software Engineer – Data Science (SSE)

 • The SSE will drive end-to-end delivery of ML and LLM-based solutions

 • The role requires strong data science execution and hands-on experience in agentic AI workflows

 • The role also requires experience with AWS-based deployment

You will own ML solutions for defined problem areas while collaborating closely with Staff engineers on architecture and standards.

This role is ideal for someone who is:
 • Strong in data science and ML systems.

 • Experienced with production ML/LLM deployments on AWS.

 • Actively building agentic AI and RAG-based solutions.

In this role, you will:

Own end-to-end ML pipelines for security use cases:
 • Malware detection models

 • Malware behaviour-based models

 • User behavioural analytics

 • Design and implement feature engineering pipelines

Build, tune, and evaluate:
 • Supervised and unsupervised ML models

 • Deep learning models (NLP-heavy workloads)

 • Design and maintain RAG pipelines using vector databases

 • Implement LLM orchestration using LangChain / LangGraph

 • Apply prompt engineering, guardrails, and governance practices

 • Fine-tune models using LoRA / PEFT where applicable

 • Deploy and operate ML/LLM systems using AWS SageMaker, Bedrock, Lambda, and EKS

 • Implement model registry, versioning, drift detection, and retraining workflows

 • Monitor production models and participate in incident response and on-call rotations

 • Mentor junior engineers and support technical execution across the team

The skills you’ll bring include:

Core
 • 5–8 years of experience as a Data Scientist or ML Engineer.

 • Strong hands-on expertise with scikit-learn, PyTorch/TensorFlow, and Pandas/NumPy.

 • Proven experience delivering production ML systems.

Strong understanding of:
 • Feature engineering

 • Model explainability (SHAP, LIME)

 • ML evaluation and tuning

 • Solid AWS experience across ML workloads

 • Agentic AI & LLM

Hands-on experience with:
 • RAG pipelines

 • LangChain / LangGraph

 • Prompt engineering and evaluation

 • Familiarity with LLM evaluation tools (Promptfoo, HELM)

 • Understanding of guardrails, governance, and observability

 • Experience in cybersecurity or threat detection

 • Operating ML systems with CI/CD, monitoring, and retraining

 • Exposure to agentic AI beyond single-agent workflows

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, we are on a mission to create a secure digital world for our customers, our industry, and our communities. We do this by embracing tenacity, passion, and collaboration to challenge what’s possible and drive extraordinary impact.
Here, we’re building a dynamic workplace where everyone can have the career experience of a lifetime. We challenge ourselves to grow to our full potential. We learn from our missteps and celebrate our victories. We come to work every day to push boundaries in cybersecurity and keep our 10,000 global customers ahead of whatever’s next.
Join us and bring your unique experiences and perspectives to tackle some of the world’s biggest security challenges.