Systems Architect, Retail and Marcom Engineering

Marcom Engineering a globally recognized engineering team ensures seamless global communications across various media and platforms. Our products and services interact with hundreds of millions of Apple customers daily enabling us to drive strategic marketing committed to continuous learning and delivering global solutions. By collaborating with diverse teams we combine expertise to create interactive experiences with talented software engineers.

As a Systems Architect youll set technical direction for cloud infrastructure delivery platforms and operational excellence programs influencing how we build ship and scale digital experiences defining the Apple brand. Your decisions impact organizations accelerate delivery for engineers and raise the ceiling on Marcom Engineerings an AI-driven world youll lead the integration of intelligent automation AI-assisted operations and LLM-powered developer tooling into our engineering processes.

Define and own the multi-year technical roadmap for DevOps infrastructure CI/CD platforms and cloud architecture standards reference designs and platform blueprints for team infrastructure tooling cloud services and AI-driven automation framework adoption considering trade-offs cost and operational company-wide initiatives to boost developer productivity expedite deployment and enhance platform reliability with clear goals and progress major infrastructure migrations platform consolidations and with SRE Security and Compliance to design the platform for reliability observability and and fix software development issues including reliability scalability and ease of development leading your team in solving these and execute platform strategies for AI/ML workload delivery including model training infrastructure LLM inference serving feature pipelines and AIOps integration. Mentor senior and staff engineers conduct architecture reviews provide design feedback and improve technical standards.

Bachelors degree in Computer Science Software Engineering or a related field or equivalent practical experience.n12 years of hands-on experience in infrastructure DevOps platform or software engineering with at least 3 years in a senior in cloud platforms (AWS GCP) including network topology identity and access management cost governance and multi-account in containerization and orchestration (Docker Kubernetes Helm Kustomize service mesh).nProficiency in infrastructure-as-code (Terraform Pulumi Ansible) configuration management state management modularity and designing and operating CI/CD systems (Jenkins Spinnaker ArgoCD GitHub Actions) and creating pipelines for large in at least two systems programming language (Python Go Java) for tooling and automation.

15 years of experience in infrastructure or platform engineering especially in fast-paced large-scale consumer-facing technology architecting end-to-end MLOps platforms including model registries experiment tracking automated retraining pipelines A/B testing infrastructure and production model in LLM infrastructure including hosting fine-tuning large language models RAG pipelines MCP server creation and integration vector databases and prompt engineering at implementing AIOps solutions that automate or augment on-call operations including predictive alerting automated root cause analysis self-healing runbooks and capacity with AI safety and governance including model drift detection bias monitoring explainability and audit of FinOps principles applied to AI workloads including GPU cost optimization spot instance strategies and inference cost building internal developer platforms with AI-assisted features like natural language queries AI-generated runbooks and LLM-augmented incident in platform modernization including bare-metal to cloud migrations monolith decomposition and legacy CI/CD with edge computing CDN architecture and globally distributed cache and content delivery strategies for large-scale web -on experience in chaos engineering and advanced reliability practices including failure injection game days capacity modeling and traffic of publishing architecture decisions internal white papers or cross-org RFCs that influenced platform to open-source infrastructure or AI/ML tooling projects or active participation in DevOps and AI engineering of application and infrastructure security (zero-trust secrets management vulnerability management compliance frameworks).nVerbal and written communication skills for presenting complex architectural trade-offs to engineering and executive and AI Certification/s