2 days ago
Responsibilities
- Develop and deploy large-scale data platforms, backend services, streaming applications, and semantic or hybrid search systems.
- Design and manage large-scale data processing pipelines using Kafka, Spark, and streaming technologies.
- Build RAG pipelines, AI agents, autonomous workflows, and production services integrating LLM and ML inference APIs.
- Automate system operations, maintain configuration and procedural documentation, and train users on complex technical topics.
- Provide incident resolution, troubleshooting, root-cause analysis, backup administration, and 24x7 on-call support for production systems.
- Improve system stability, security, efficiency, scalability, uptime, and availability while planning future capacity and evaluating new technologies.
- Manage observability, logging, monitoring, and operational excellence for distributed systems across cloud and on-premises environments.
- Collaborate cross-functionally with program managers, engineering partners, Apple staff, and management.
Requirements
- At least 5 years of software development and deployment experience in Kubernetes environments.
- At least 3 years of experience deploying applications using Ansible, Docker, Jenkins, or related tools.
- At least 5 years of experience building robust HTTP REST-based APIs and backend services.
- Experience building highly available software services or platforms in the big data space.
- Experience designing and managing large-scale data processing pipelines using Kafka, Spark, and streaming technologies.
- Proficiency in Python, with optional experience in Go and Java.
- Bachelor's degree in Computer Science or Computer Engineering, or equivalent work-related experience.
- Preferred: master's degree in Computer Science or equivalent and at least 5 years of industry experience designing and managing large-scale production deployments.
- Experience with software design, testing, source code management, CI/CD, open-source development, automation, and operational excellence.
- Experience with embedding models, LLMs, pre-training, fine-tuning, ETL pipelines, measurable SLAs, near-real-time data processing, RAG, AI agents, and ML inference in production services.
- Expertise with Docker, Kubernetes, Helm, Kustomize, Flux or GitOps practices, Ansible, Terraform, and Crossplane.
- Proficiency with Linux/POSIX operating systems, shell scripting, networking, distributed databases, logging, observability, and cloud service monitoring.
- Experience using Kubernetes probes, Splunk, Prometheus, Grafana, Mosaic, ETCD, Kafka, and Spark in large-scale production systems.
- Strong troubleshooting, communication, collaboration, architectural, and problem-solving skills.
Benefits
- 24x7 on-call support is part of the role.
- The position supports deployments across on-premises and multiple cloud environments.
- The team emphasizes cultural diversity, collaboration, automation, documentation, and operational excellence.
Tech Stack
AnsibleApache FlinkApache KafkaApache SparkAWSDockerGoGoogle Cloud PlatformGrafanaHelmJavaJenkinsKubernetesLinuxPrometheusPythonSplunkSQLTerraform
Categories
Data EngineeringDevOps
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.