Software Site Reliability Engineer - AI & Data Platforms

Description

Minimum 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).

Preferred Qualifications

• 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.