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Software Site Reliability Engineer - AI & Data Platforms

Apple· IS&T (Information Systems and Technology) / AI & Data Platforms (AiDP)
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Hybrid (Bengaluru)full-timePosted 1mo ago

About the role

Data Platform SRE responsible for developing and operating Apple’s big data platform to support analytics, reporting, and AI/ML applications. Focus on reliability, scalability, performance, cost optimization, automation, incident resolution, and collaborating with development and operations teams to embed reliability across the software lifecycle.

Responsibilities

  • Design, develop, and automate: Build tools, frameworks and solutions to improve reliability, scalability, and efficiency across large scale distributed data platform systems.
  • Monitor and maintain: Implement advanced monitoring and alerting for on-prem, cloud and workloads.
  • Troubleshoot and solve: Support critical applications including analytics, reporting, and AI/ML apps. Respond to and resolve complex production incidents, and perform root cause analysis.
  • Collaborate: Work closely with development and operations teams to integrate reliability best practices throughout the software lifecycle.
  • Optimize: Proactively recommend improvements in architecture, deployment, and operations for distributed systems

Qualifications

  • Experience: 3+ years in software site reliability engineering or software development roles.
  • Programming: Proficient in at least one of Python, Golang, or Java.
  • Skilled at coding for distributed systems and developing resilient data pipelines.
  • Cloud Platforms: Hands-on experience with at least one major cloud platform (AWS, Azure, or Google Cloud Platform).
  • Expertise in designing, building, and operating critical, large-scale distributed systems with a focus on low latency, fault-tolerance, and high availability.
  • Experience with contribution to Open Source projects is a plus.
  • Experience with multiple public cloud infrastructure, managing multi-tenant Kubernetes clusters at scale and debugging Kubernetes/Spark issues.
  • Experience with workflow and data pipeline orchestration tools (e.g., Airflow, DBT).
  • Understanding of data modeling and data warehousing concepts.
  • Familiarity with the AI/ML stack, including GPUs, MLFlow, or Large Language Models (LLMs).
  • Data Structures & Algorithms: Strong foundation and application experience.
  • Distributed Systems: Solid understanding and hands-on experience managing at least one distributed system (e.g. Kafka, Spark, Flink etc.).
  • Solid understanding of software engineering best practices, including the full development lifecycle, secure coding, and experience building reusable frameworks or libraries.
  • Problem Solving: Demonstrated ability to independently troubleshoot and resolve complex technical issues.
  • Creative Thinking: A track record of proposing and implementing innovative solutions to technical challenges.

Skills

Required:PythonGolangJavaDistributed systems

Benefits

  • Accessibility-focused culture and benefits
Last updated Sep 4, 2026. Interested? Apply on the company site.

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