Principal Software Engineer

Job Description: Principal Software Engineer, AI-SOC Rapid7 is seeking a Principal Software Engineer, AI-SOC to serve as a technical anchor on the team building the autonomous investigation platform at the core of our MDR service. This is a hands-on, high-impact role for an engineer who brings deep expertise in data systems, distributed architecture, and ML/AI and who wants to apply that expertise to a domain where the stakes are real. About The Team The AI-SOC engineering team sits within Rapid7's Detection & Response organization and builds the autonomous investigation platform powering our MDR service. Operating at the intersection of managed security operations and agentic AI, the team develops capabilities that triage alerts at machine speed so analysts can focus on high-value decisions. The team spans ML/AI engineering, data engineering, and platform engineering, tackling hard problems in real-time data processing, investigation orchestration, and intelligent disposition. About The Role As a Principal Software Engineer, AI-SOC, your primary responsibility will be to drive the technical design and delivery of the foundational systems that make autonomous investigation possible at scale. Specifically, your focus will be to: Architect and implement core platform components across the AI-SOC stack, including data ingestion pipelines, query engines, investigation orchestration, and ML model integration layers.Own technical direction for the team's most complex and ambiguous problems, defining interfaces, data contracts, and system boundaries that scale reliably across diverse alert types and log sources.Partner with ML/AI engineers to design the infrastructure that trains, serves, and evaluates disposition models, ensuring tight feedback loops between production signals and model improvement.Establish and champion engineering standards across the team: system design patterns, data modeling conventions, testing practices, and observability requirements.Lead design reviews and provide deep technical mentorship to senior and staff engineers, raising the overall technical ceiling of the team.Identify and resolve systemic performance, reliability, and scalability bottlenecks across the distributed investigation pipeline.Collaborate with Product Management to shape requirements, surface technical constraints early, and propose solutions that balance speed with long-term platform health.Contribute to cross-team architectural decisions and represent AI-SOC engineering in broader platform and infrastructure forums. The Skills And Qualities You'll Bring Include Bring 10+ years of software engineering experience, with a demonstrated track record of leading complex, high-scale system design across distributed environments.Demonstrate deep expertise in data systems, including stream processing (e.g., Kafka, Flink), distributed query engines, data modeling, and storage systems (e.g., DynamoDB, S3, data mesh patterns).Apply strong working knowledge of ML/AI system design, including model serving infrastructure, feature pipelines, embedding systems, or LLM integration. You don't need to be a data scientist, but you need to build confidently alongside them.Proven experience designing systems where correctness, latency, and throughput all matter. You think carefully about trade-offs and can articulate them clearly.Excel at taking ownership of ambiguous, cross-cutting technical problems and driving them to well-reasoned, well-documented solutions.Demonstrate experience working in cloud-native environments (AWS preferred), with strong command of infrastructure patterns relevant to AI/ML workloads.Familiarity with security operations, detection engineering, or threat intelligence pipelines is a plus, intellectual curiosity about the domain is required.Build strong working relationships with product, data science, and platform engineering peers, and communicate technical concepts clearly to non-engineering stakeholders.Bring strong written and ver