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 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 verbal communication skills; you write clear design docs, give direct feedback, and can align stakeholders around technical direction.
• 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.