We’re looking for an exceptional automation engineer to build the pipeline that scales security review across Apple’s 1000s+ services. You will turn security expertise into running software, designing and operating AI agentic review system, skills, tool layer, evaluation harness on top of Apple's existing security tooling, and giving reviewers a reliable, high-throughput pipeline to execute against. You’ll partner closely with the security engineers who define the review standards and the analysts who validate the output, and build automation that reduces toil.

Minimum Qualifications
1 year of building LLM- or agent-based systems that ran in production, with a measured quality bar
8+ years building and operating production automation, data pipelines, or backend services
Highly proficient in at least one of Python, Go, or Java
Experience integrating third-party and first-party APIs, tooling, and services into reliable end-to-end workflows and AI agent workflows
Working knowledge of application and cloud security concepts (threat modeling, vulnerabilities, secure configuration)
MS or BS or equivalent experience in Computer Science, Engineering, or a related field OR equivalent practical experience in Software or Security Engineering

Preferred Qualifications
Experience with Agent engineering: retrieval, grounding, citation, reasoning
Experience with Agentic workflow design with bounded autonomy, building LLM- or agent-based automation and evaluating output quality (precision/recall, human-in-the-loop feedback loops), AI agent evaluation harness as CI
Familiar with AWS cloud resources (S3, EC2, Lambda, Step Functions, etc.)
Experience with security tooling such as SAST/SCA scanners, SBOM tooling, or vulnerability intelligence platforms
Background in security review, threat modeling, or supply-chain security
Experience delivering tooling used by non-engineer reviewers or contractors at scale
Awareness of AI-specific threats in systems that ingest untrusted input