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 leverage AI/ML for enhanced customer security and threat detection. We operate with a creative, iterative approach, building on 20+ years of threat analysis and a growing patent portfolio. We foster a collaborative environment, sharing knowledge, developing internal learning, and encouraging research publication. If you're passionate about AI and want to make a major impact in a fast-paced, innovative environment, this is your opportunity.
The technologies we use include:• Python is used for analysis and modelling, with numpy, pandas, and scientific computing libraries.• Jupyter notebooks are used for local and remote analysis.• scikit-learn is used for machine learning.• Anomaly detection is used for large-scale unlabeled data analysis.• LLM/GenAI toolchains, including HuggingFace, Transformers, LangChain, CrewAI, and Agentic architectures, are used.• The AWS cloud ecosystem, including SageMaker, Bedrock, Lambda, EKS, and S3, is used.• Agentic AI platforms, including multi-agent orchestration, tool use, reasoning frameworks, and LLMOps, are used.• EKS is used for application deployment.• Terraform is used for infrastructure as code.
About the Role
Rapid7 is seeking a Staff AI Engineer to join our Data Science team as we expand and evolve our growing AI and MLOps efforts. You should have a strong foundation in software engineering and applied R&D in one of the key areas we focus on - traditional machine learning, neural networks, or generative AI. In this intersectional role, you will combine your expertise in AI/ML deployments, cloud systems and software engineering to enhance our product offerings and streamline our platform's functionalities.
This role is ideal for someone who is:• Strong background in data science.• Proficient with AWS and ML/LLM infrastructure.• Excited about agentic AI, autonomous workflows, tool-augmented LLM systems, and building the future of AI-driven security.
In this role, you will:• Work with security teams to define, scope, and design research efforts for new threat detections, automations, and AI-driven workflows.• Collaborate with data scientists to transform research into production-ready solutions, mentoring on both methods and execution.• Research, build, and evaluate ML and generative/LLM models, including agentic and multi-step reasoning systems.• Design and optimise agentic architectures, including tool-calling, decision-making, memory, orchestration, and evaluation frameworks.• Partner with engineering teams to ship AI features, integrating models into high-scale systems.• Deploy AI/ML workloads in AWS using SageMaker, Bedrock, Lambda, EKS, Step Functions, and related services.• Contribute to our LLMOps and MLOps workflows, improving evaluation pipelines, observability, reproducibility, and governance.• Support development of AI security features, improving reasoning, context understanding, automation, and analyst workflows.• Embrace agile development, iterative experimentation, and collaborative problem solving.• Mentor junior team members and uplift the technical bar for agentic AI and ML engineering.
The skills you'll bring include:
Core• 8-12 years of experience as a Data Scientist, ML Engineer, or AI Engineer.• Strong end-to-end practical expertise in ML/AI/DS.• Able to explore, experiment, and deliver independently.
Proficiency in:• scikit-learn is used for classical machine learning.• PyTorch, TensorFlow, and Keras are used for deep learning.• HuggingFace, LangChain, and Transformers are especially useful for LLMs.• Pandas and NumPy are used for data preparation.• A clear understanding of modelling approaches and their suitability for different problems is necessary.• Strong communication skills and the ability to present technical concepts to diverse audiences are important.• The ability to collaborate across engineering, data science, product, and security teams is necessary.• Experience mentoring and guiding junior data scientists is preferred.• Agentic AI and LLM expertise is highly preferred.• Hands-on experience with agentic AI architectures, such as CrewAI, LangGraph, LangChain agents, tool-calling, and function-chaining, is preferred.• Experience building multi-step reasoning workflows, autonomous agents, or LLM-powered decision systems is preferred.• Understanding of prompt engineering, evaluation frameworks, LLM observability, and guardrails is preferred.• Experience working with AWS Bedrock, model selection, latency/cost trade-offs, and LLM deployment patterns is preferred.• AWS and cloud experience is highly preferred.
Strong experience in AWS ML ecosystem:• SageMaker training & inference• Bedrock LLM integrations• Lambda for serverless workflows• EKS for containerized deployments• S3, Glue, Athena, IAM best practices• Experience with Terraform, IaC, and production deployment workflows
Experience with the following would be advantageous:• Experience in the security industry• Deployment of AI and machine learning models• Implementing model risk management strategies, including model registries, concept/covariate drift monitoring, and hyperparameter tuning
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 then please apply
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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 11,500+ 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.
Skills Required
- 8-12 years of experience as a Data Scientist, ML Engineer, or AI Engineer
- Proficiency with AWS and ML/LLM infrastructure
- Strong end-to-end practical expertise in ML/AI/DS
- Experience mentoring junior data scientists
- Hands-on experience with agentic AI architectures
- Experience building multi-step reasoning workflows
- Understanding of prompt engineering and evaluation frameworks
- Experience in the security industry
Rapid7 Compensation & Benefits Highlights
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Healthcare Strength — Health coverage spans medical, dental, and vision, supplemented by mental-health resources, FSAs, and optional pet insurance. Inclusive elements such as transgender‑inclusive care, abortion‑travel support, and neurodiversity coverage broaden access.
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Leave & Time Off Breadth — Time off includes unlimited PTO in the U.S., paid sick time, paid holidays, wellness days, bereavement, and paid volunteer time. Hybrid‑first flexibility and periodic company days off reinforce work–life support.
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Parental & Family Support — Parental support features generous paid leave and fertility benefits alongside backup childcare via Care.com. Dedicated mother’s rooms and family medical leave indicate attention to caregiving needs.
Rapid7 Insights
What We Do
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.
Why Work With Us
With our products, research, and open source communities, we’re building a secure digital future for everyone. This means constantly learning and evolving in an industry that’s anything but stagnant. You’ll be faced with tough challenges, and given the support to find creative solutions that drive our business, and your career forward.
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Rapid7 Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Our default working model is hybrid, with employees working three days per week in the office. This approach underpins our commitment to flexibility and adaptability while supporting our dedication to development, teamwork and customer purpose.

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