DevOps Software Engineer - Security Research, SEAR

A strong candidate for this role is passionate about building reliable, secure, and scalable infrastructure that directly amplifies security research impact. You will work closely with security researchers, located worldwide, to transform internal research tools — including binary analysis frameworks, static analysis pipelines, and ML-powered data intelligence engines — into robust production services used by teams across Apple. You will own the complete journey: from evaluating prototype readiness and hardening codebases for scale, through deployment, to ongoing reliable operation. On the development side, you will assess existing research codebases for production readiness, extend and improve them for scale, and build the service APIs and integrations that make them accessible to a broader audience. On the infrastructure side, you will design containerized deployments, establish CI/CD pipelines, implement secrets management and access controls, and build monitoring and observability practices that keep platforms performant and security. Minimum Qualifications Experience designing and operating cloud and on-premises service infrastructure, with advanced knowledge of containerization, Kubernetes, data storage, networking, authentication/authorization (OIDC, OAuth), queuing, logging, and monitoring. Advanced knowledge in scripting and programming languages, including Python and Bash. Experience with CI/CD pipelines and automation tooling (e.g., Jenkins, GitHub Actions, or equivalent), and observability stacks (e.g., Prometheus, Grafana, OpenSearch/ELK). Self-starter with strong ownership, accountability, and ability to work autonomously and collaboratively across teams and organizations in a fast-paced environment. Preferred Qualifications Experience building or operating security research tooling Experience with and/or strong enthusiasm for security, especially offensive security Prior experience working with large-scale data pipelines and storage systems Familiarity with AI/ML workflows and agents;