# Lead, Engineering Backup at MongoDB

MongoDB is hiring a Lead, Engineering Backup in New York, United States. It pays $137k-$270k a year and Level rates it Little AI ●○○○; you can [apply on MongoDB](https://jobsbylevel.com/go/cdf1eb0d-5d81-4ff2-985a-bc9d98b267cc?utm_medium=ai-agent).

AI Level 1, AI centrality 37 out of 100. New York.

## Details

- Company: [MongoDB](https://jobsbylevel.com/companies/mongodb)
- AI level: AI Level 1 (score 37 out of 100)
- Location: New York
- Salary: $137k-$270k
- Posted: November 5, 2026
- Apply: https://jobsbylevel.com/go/cdf1eb0d-5d81-4ff2-985a-bc9d98b267cc?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=lead-engineering-backup-at-mongodb-2fa4a8

## Description

Engineering Manager, Atlas Infinite Backup New York City MongoDB powers mission-critical workloads for customers who expect their data to be durable, recoverable, and fast to access. Atlas Infinite is our next-generation cloud-native architecture that decouples compute from storage, and its storage layer continuously backs every cluster up to cloud object storage. The Atlas Infinite Backup team builds the systems that turn that stream of data into something customers can trust: point-in-time recovery, retained snapshots, fast restores, disaster recovery, and backup storage that stays affordable as clusters grow to hundreds of terabytes. We are hiring an Engineering Manager to lead this team. This is a hands-on leadership role for someone who takes the responsibility of durably storing and recovering customer data seriously, is comfortable with the economics of large-scale storage, and has strong empathy for both their team and our users. About the Atlas Infinite Backup team The team is part of MongoDB's Backup and Object Storage Services organization and works hand in hand with Storage Layer Services, the disaggregated storage layer behind Atlas Infinite. We own the object storage tier: everything that happens to a cluster's data after it leaves the hot path and lands in cloud object storage. Because backup is a property of the storage layer rather than a separate agent copying files, the team works on the storage engine's write path, data layout, and lifecycle as much as on backup features. The team's responsibilities include: Continuous backup of log and page data to object storage, and the indexing that lets a cluster's full history be located and read efficiently Point-in-time recovery, snapshot retention, and restore for clusters at the scale of 100+ TB per shard, including cluster-level and collection-level restore Compaction and garbage collection of the object store so that retained history costs what it should and no more Cold data: serving and tiering infrequently accessed collections and indexes directly from object storage Metering and billing for backup storage, including the model that decides what customers pay for retained snapshots and point-in-time recovery Disaster recovery and compliance capabilities for Atlas Infinite, such as cross-region protection, retention policies, and data lifecycle guarantees Operating these services in production across many cells and regions: observability, on-call, capacity, and cost What you'll do Lead, grow, and manage a team of 6 engineers working in Rust and Java on distributed storage systems; set clear expectations, high standards, and healthy, sustainable execution Own the team's roadmap across durability, recoverability, cost efficiency, and compliance, in partnership with Backup and Object Storage Services leadership and Product Management Drive the Atlas Infinite backup roadmap to GA and beyond: define what done means for disaster recovery, compliance, and backup economics, and sequence the work to get there Manage customer escalations involving backup, restore, or backup cost; work with Support, Atlas, and server teams to reproduce, root-cause, and resolve issues Partner closely with the WiredTiger storage engine team, the Storage Layer Services teams that own the Log Service and Page Materializer, Atlas Backup, Atlas Billing, and Pricing & Packaging on cross-team features such as incremental billing, collection-level restore, and cold collections Raise the bar on engineering practice: design reviews, operational readiness, incident follow-through, and the tooling that lets a small team run a large production footprint Represent the team in planning, staffing, and calibration; make thoughtful tradeoffs between near-term GA deliverables, long-term architecture, and operational investments Candidate profile 8+ years building, debugging, and operating distributed storage, database, or large-scale data infrastructure systems (storage engines, object storage, backup and

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Source: https://jobsbylevel.com/jobs/lead-engineering-backup-at-mongodb-2fa4a8

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