AI Engineer
Role details
Job location
Tech stack
Job description
- As a leader in cybersecurity, Rapid7 is expanding our global AI footprint and is looking for a passionate Senior AI Engineer to join Rapid7's AI Centre of Excellence. The AI centre of excellence is on a mission to use AI to accelerate threat investigation, detection and response (D&R) capabilities of our Security Operations Centre (SOC) for both conventional networks and cloud environments. You should be ready to design and deliver solutions that address complex, unsolved challenges, working closely with development teams, data engineering, product managers and UI/UX teams along the way. About the Team The AI Center of Excellence team designs, prototypes and ships production AI models and systems. Our mission is to leverage the best available technology to protect our customers' attack surfaces. For example, we partner closely with Rapid7's 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. The environment is collaborative, sharing knowledge and developing internal learning. 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:
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AWS for hosting our research environments, data, and features (i.e. Sagemaker, Bedrock)
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EKS to deploy applications
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Terraform to manage infrastructure
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Python for analysis and modeling, taking advantage of numpy and pandas for data wrangling.
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Jupyter notebooks (locally and remotely hosted) as a computational environment
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Sci-kit learn for building machine learning models
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Anomaly detection methods to make sense of unlabeled data, Rapid7 is seeking a Staff AI Engineer to join our team as we expand and evolve our growing AI and MLOps efforts. You should have a strong foundation in software engineering, and MLOps and DevOps systems and tools. Further, you'll have a demonstrated track record of taking models created in the AI R&D process to production with repeatable deployment, monitoring and observability patterns. 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. Specifically, your focus will be to:
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Design and build ML production systems, including project scoping, data requirements, modeling strategies, and deployment
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Develop and maintain data pipelines, manage the data lifecycle, and ensure data quality and consistency throughout
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Assure robust implementation of ML guardrails and manage all aspects of service monitoring
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Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations
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Share expertise and knowledge consistently with internal and external stakeholders, nurturing a collaborative environment and fostering the development of junior engineers
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Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios.
Requirements
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8-12 years experience as a Software Engineer, with at least 3 years focused on gaining expertise in ML deployment (especially in AWS)
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Solid technical experience in the following is required: o Software engineering: developing APIs with Flask or FastAPI, paired with strong Python knowledge o DevOps and MLOps: Designing and integrating scalable AI/ML systems into production environments, CI/CD tooling, Docker, Kubernetes, cloud AI resource utilization and management o Pipelines, monitoring, and observability: Data pre-processing and feature engineering, model monitoring and evaluation
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A growth mindset - welcoming the challenge of tackling complex problems with a bias for action
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Proven ability to collaborate effectively across engineering, data science, product, and other teams to drive successful MLOps initiatives and ensure alignment on goals and deliverables.
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Familiarity with resources that enable data scientists to fine tune and experiment with LLMs
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Knowledge of or experience with model risk management strategies, including model registries, concept/covariate drift monitoring, and hyperparameter tuning
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Enjoy mentoring and elevating the technical performance of your peers
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Demonstrate curiosity and persistence - you're excited to explore new techniques, tools, and ideas while maintaining focus on reliability and value
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Balance autonomy with accountability, with a strong sense of ownership for delivering AI capabilities that make measurable impact
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Strong written & verbal communication with the ability to convey complex ideas clearly to both technical and non-technical audiences
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Approaches change with openness and curiosity, seeking to understand the "why" and helping teams adapt quickly and effectively
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Core Value Embodiment: Embody our core values to foster a culture of excellence that drives meaningful impact and collective success. 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.
