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 experiences.\\nWe're 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, you'll 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 Engineering's technology.\nIn an AI-driven world, you'll lead the integration of intelligent automation, AI-assisted operations, and LLM-powered developer tooling into our engineering processes.
Bachelor's 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 role.\nExpertise in cloud platforms (AWS, Google Cloud Platform), including network topology, identity and access management, cost governance, and multi-account strategy.\nProficiency in containerization and orchestration (Docker, Kubernetes, Helm, Kustomize, service mesh).\nProficiency in infrastructure-as-code (Terraform, Pulumi, Ansible), configuration management, state management, modularity, and GitOps.\nExperience designing and operating CI/CD systems (Jenkins, Spinnaker, ArgoCD, GitHub Actions) and creating pipelines for large teams.\nProficiency 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 environments.\nExperience architecting end-to-end MLOps platforms, including model registries, experiment tracking, automated retraining pipelines, A/B testing infrastructure, and production model observability.\nExpertise in LLM infrastructure, including hosting, fine-tuning large language models, RAG pipelines, MCP server creation and integration, vector databases, and prompt engineering at scale.\nExperience implementing AIOps solutions that automate or augment on-call operations, including predictive alerting, automated root cause analysis, self-healing runbooks, and capacity forecasting.\nFamiliarity with AI safety and governance, including model drift detection, bias monitoring, explainability, and audit trails.\nUnderstanding of FinOps principles applied to AI workloads, including GPU cost optimization, spot instance strategies, and inference cost modeling.\nExperience building internal developer platforms with AI-assisted features like natural language queries, AI-generated runbooks, and LLM-augmented incident postmortems.\nExperience in platform modernization, including bare-metal to cloud migrations, monolith decomposition, and legacy CI/CD re-platforming.\nExperience with edge computing, CDN architecture, and globally distributed cache and content delivery strategies for large-scale web properties.\nHands-on experience in chaos engineering and advanced reliability practices, including failure injection, game days, capacity modeling, and traffic shaping.\nRecords of publishing architecture decisions, internal white papers, or cross-org RFCs that influenced platform direction.\nContributions to open-source infrastructure or AI/ML tooling projects, or active participation in DevOps and AI engineering communities.\nGrasp 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 audiences.\nCloud/DevOps and AI Certification/s
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: d5b82e5e65dc7397567e93c6a13b9055
- Posted 6 days ago
Never miss an opportunity! Create an alert based on the job you applied for.
