Sr. Platform Software Engineer, AI & Data Platforms (AiDP)

People at Apple don’t just build products - they craft the kind of experience that have revolutionized entire industries. The diverse collection of our people and their ideas inspire innovation in everything that we do. Imagine what you could do here! Join Apple, and help us leave the world better than we found it.

Data powers Apple's software, services, and product development. Apple's Data Services Org. provides a diverse range of data solutions, including SQL and NoSQL databases, search engines, and streaming platforms with GenAI capabilties. Apple’s Data Services team supports building data platforms for several large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business, we manage many streams of Apple-scale data. We bring it all together and extract the insights & value. We do all this with an exceptional group of software engineers, data scientists, SRE/DevOps engineers, and managers. We are looking for a talented and dedicated senior big data engineer to join our team to bring passion for infrastructure and distributed systems to build world-class data platforms/products at a very large scale across multiple cloud environments running on S3, Kafka, Flink, Spark, LLMs and AI/ML! You would work on developing/deploying large-scale big data semantic/hybrid search, streaming applications.

Description

What are we expecting? The ideal candidate will bring a lot of energy, innovation and excitement! Will be ready to learn and explore cutting edge technologies in distributed computing and big data.

You like to automate anything which you do and you document it for the benefit of others. You are an independent problem-solver who is self-directed and capable of exhibiting deftness to handle multiple simultaneous competing priorities and deliver solutions in a timely manner. Provide incident resolution for all technical production issues. Create and maintain accurate, up-to-date documentation reflecting configuration, and responsible for writing justifications, training users in complex topics, writing status reports, documenting procedures, and interacting with other Apple staff and management. Provide guidance to improve the stability, security, efficiency, and scalability of systems. Determine future needs for capacity and investigate new products and/or features. Strong troubleshooting ability will be used daily; will take steps on their own to isolate issues and resolve root causes through investigative analysis in environments where the candidate has little knowledge/experience/documentation. Administer and ensure the proper execution of the backup systems. Provide 24x7 on-call support to handle urgent critical issues. We are dedicated to the goal of building a culturally diverse and pluralistic team that reflects the multicultural variety of our customers.

Minimum Qualifications

5+ years of software development & deployment experience in kubernetes environment; with 3+ years in deploying applications using Ansible, Docker, Jenkins or related tools

5+ years building robust HTTP REST based API's and backend services

Experience in building highly available software services or platform in big data space

Experience in designing and managing large scale data processing pipelines using Kafka, Spark and streaming technologies

Proficient in Python, optionally in Go & Java

Bachelor's in Computer Science or Computer Engineering or equivalent work related experience

Preferred Qualifications

MS in Computer Science or equivalent with 5+ years of overall industry experience in designing and managing large-scale production deployments (On-Prem and AWS/GCP).

Validated experience in software design, testing, and source code management. Experience with Python and/or Go development; Strong background in CI/CD practices and open-source software development. Passionate about operational excellence through proper automation and engineering processes using programming languages such as Go, Python, Java, or other JVM languages. (any one)

Experience with public Embedding models and Large Language Models (LLMs), including expertise in pre-training, fine-tuning, and optimizing data insights for accuracy and recall. Experience managing ETL pipelines, designing measurable SLAs, and handling near-real-time upstream/downstream data processing. Design and implementation of RAG pipelines, AI Agents with crew ai API and autonomous workflows. Familiarity with AI/ML tooling - LLM APIs, integrating ML inference into production services

Expertise in Docker, Kubernetes (or equivalent), Helm, and Kustomize via Flux/or GitOps practices.Infrastructure as Code (IaC): Experience with tools like Ansible, Terraform, and Crossplane. Proactive mindset with a sharp focus on improving uptime and availability for mission-critical services. Proficiency in Linux/POSIX operating systems, shell scripting, and networking technologies. Experience in managing and monitoring large scale cloud services using Kubernetes probes, Splunk, Prometheus, Grafana, and Mosaic. Mastery of logging and observability technologies to track system metrics. Familiarity in monitoring cloud services using Kubernetes probes, Splunk, Prometheus, Grafana, and Mosaic.

Ability to handle architectural considerations like performance, scalability, reusability, and flexibility in distributed databases. Ability to handle architectural considerations like performance, scalability, reusability, and flexibility in distributed databases. Familiarity with ETCD, Kafka and Spark in large scale production systems.

Proactive mindset with a sharp focus on improving uptime and availability for mission-critical services. Communication skills to collaborate cross-functionally with program managers and engineering partners. Comfortable working in fast-paced environments while continuously evaluating emerging technologies.