Principal AI/ML Engineer

Principal LLM Engineer
Join Rapid7: Secure the Future with AI
Are you ready to lead the charge in integrating cutting-edge Large Language Models (LLMs) into world-class Cyber Security products?
Rapid7 is looking for a Principal LLM Engineer with a rare combination of deep Data Science expertise, mastery of production MLOps, and 13+ years of experience. You won't just build models; you'll architect the AI systems that protect our customers from the world's most sophisticated threats. This is a role for a proven leader who turns breakthrough research into scalable, high-impact security solutions.
What You'll Be Doing: Technical Leadership
As a Principal Engineer, you will define and execute the technical strategy across three critical domains:
1. LLM & AI System Architecture
You'll design and build the next generation of AI-powered security features.

• LLM Orchestration: Architect complex security applications using frameworks like LangChain and LangGraph to connect LLMs with our data and tools.
• RAG Pipelines: Build and optimise high-performance Retrieval-Augmented Generation (RAG) systems using Vector DBs to give our AI the context it needs from vast security datasets.
• Model Optimisation: Implement efficient adaptation techniques (LoRA/PEFT) and run rigorous evaluation using tools like Promptfoo/HELM to ensure model accuracy and safety.
• Governance & Safety: Design and enforce security Guardrails and governance policies for all LLM deployments.

2. Security-Focused MLOps & Production
You'll ensure our AI is always live, stable, and fighting threats.

• Real-Time Monitoring: Establish comprehensive monitoring with Prometheus/Grafana/CloudWatch and lead our response to production incidents (PagerDuty, On-call).
• Model Life Cycle: Master the MLOps pipeline, from model versioning (MLflow/SageMaker) to automating Drift Detection & Retraining.
• Infrastructure: Use Terraform and Docker/Kubernetes to deploy scalable microservices and APIs.
• Cloud Security Integration: Leverage AWS Bedrock/SageMaker/Lambda and ensure all deployments adhere to the highest standards of Cloud Security (IAM, VPC, Secrets).
• CI/CD: Drive continuous deployment for our AI systems using tools like GitHub Actions/Jenkins.

3. Data Science & Security Foundation
Your background will enable you to solve complex security problems with data.

• Deep Learning: Apply expertise in NLP, CNN, RNN, etc. to analyse security data (logs, network traffic, etc.).
• Security Models: Drive the development of Malware Detection models, User behavioural models, and Malware behaviour-based Models.
• Data Engineering: Lead initiatives in Data Acquisition, Feature Engineering, and transformation across services like S3, DynamoDB, and Redshift.
• Explainable AI (XAI): Use SHAP/LIME to ensure transparency and explainability in security decisions made by AI.

What You'll Bring

• 13+ years of professional experience in Data Science, with a significant focus on LLMs/NLP and production MLOps.
• Advanced degree (Master's or PhD) in Computer Science, Data Science, or a related field, or equivalent practical experience.
• A proven track record of taking complex ML/LLM projects from concept to highly available production systems.
• Familiarity with Cost Optimisation (FinOps) for cloud resources.

If you thrive on solving the hardest problems in AI and applying that power to make the world a safer place, we want to hear from you!