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Sonatype

Verified Job Source

AI-driven DevSecOps

Fulton, MD

Software Development
501–1,000 people

About

The Sonatype journey started 15 years ago, just as the concept of “open source” software development was gaining steam. From our humble beginning as core contributors to Apache Maven, to supporting the world’s largest repository of open source components (Central), to distributing the world's most popular repository manager (Sonatype Nexus Repository), we’ve played a meaningful role in helping the world embrace the power of open innovation. Over time, we witnessed the staggering volume and variety of open source libraries that began flowing into every development environment in the world. We understood that when open source components are properly managed, they provide a tremendous energy for accelerating innovation. Conversely, when unmanaged, open source "gone wild"​ can lead directly to security vulnerabilities, licensing risks, enormous rework, and waste. Our vision today is simple. We are laser focused on helping organizations continuously harness all of the good that open source has to offer, without any of the risk. In order to do this, we have invested in knowing more about the quality of open source than anyone else in the world. This investment takes the form of machine learning, artificial intelligence, and human expertise, which in aggregate produces highly curated intelligence that is infused into every Sonatype product. Organizations equipped with Sonatype products make better decisions, innovate faster at scale, and rest comfortably knowing that their applications always consist of the highest quality open source components.

Open positions

Staff Software Engineer

Remote · Canada

Design and maintain backend services for product provisioning, licensing, and purchasing capabilities. Lead technical architectural decisions and mentor other engineers while improving cloud infrastructure and service reliability.

Senior Data Scientist

Remote · Canada

You will provide technical leadership for applied AI and data science initiatives, guiding complex projects from concept to production. You will also act as a senior consultant to cross-functional teams to identify high-value opportunities and establish best practices for AI and GenAI solutions.

Senior Data Analyst

Remote · Canada

Transform complex product datasets into actionable insights and build scalable analytics infrastructure to drive data-informed product decisions. The role involves owning the end-to-end analytics lifecycle and mentoring associate-level analysts.

Staff Software Engineer

Remote · Canada

You will design, develop, and maintain backend services that power product provisioning, licensing, and purchasing capabilities. Additionally, you will collaborate with cross-functional teams to drive architectural decisions and mentor other engineers to ensure high-quality code delivery.

Staff Software Engineer

Remote · Canada

Design, develop, and maintain backend services that support product provisioning, licensing, and purchasing capabilities. Collaborate with cross-functional teams to improve system reliability, observability, and operational excellence while mentoring other engineers.

Staff Data Engineer

Remote · Canada

You will design, build, and maintain scalable data pipelines and ETL/ELT processes while architecting data models for analytics and operational use. Additionally, you will collaborate with cross-functional teams to evolve the data platform and implement observability and data quality monitoring.

Senior Data Analyst

Remote · Canada

The Senior Data Analyst will transform complex product datasets into actionable insights and build scalable analytics infrastructure. They will also partner with cross-functional stakeholders and mentor associate-level analysts to drive data-informed product decisions.

Data Scientist

Remote · Canada

You will lead applied AI projects from concept to impact, acting as an internal consultant to help teams deploy practical machine learning and generative AI solutions. You will also design robust experiments, build evaluation pipelines, and bridge the gap between research and production to ensure scalable, secure AI systems.