MongoDB is re-architecting its cloud storage layer through its Storage Layer Services (SLS) team. The role involves partnering with teams to define SLOs, shape capacity plans, and ensure the reliability of the storage layer that supports MongoDB Atlas.
Responsibilities:
- Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs
- Build for reliability, making services and infrastructure available, resilient, fault-tolerant, and self-healing
- Identify and configure key metrics to detect incidents and quantify service health, availability, and performance
- Participate in a 24/7 on-call rotation to resolve issues involving the storage infrastructure
- Become an expert in infrastructure performance, helping us optimize from the application level all the way to the kernel
Requirements:
- Have 6+ years of experience working on software development and operating distributed systems
- Proficiency in Python, Go, or a similar language
- Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs
- Possess a customer-focused mindset
- Value efficiency in processes and operations
- Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil
- Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market
- Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure
- Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing)
- Leading major architectural shifts, such as moving from legacy storage stacks to new multi-tenant storage architectures, including planning and executing large-scale data and workload migrations with tight availability and durability requirements
- Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure)
- Designing secure, multi-tenant runtime environments at scale