Senior Software Engineer, Storage - Distributed Caching

DoorDash USA•Seattle, WA

13h•$159,800 - $235,000•Hybrid

About The Position

The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Caching team owns every caching offering at DoorDash end to end, including ElastiCache (Redis/Valkey), Boulder (our KVRocks-based key-value store for high-QPS feature serving), Entity Cache, and the Distributed Lock Service, plus the smart clients (asgard-redis, valkey-go) that sit in front of them. These systems back critical product surfaces across DoorDash, Wolt, and Deliveroo. The team owns provisioning of clusters and the smart clients that sit in front of them, baking in sensible defaults so that other engineering teams get a turnkey caching solution instead of having to run their own. You'll help drive Boulder's evolution to scale further, improve cost efficiency, enhance performance, and support real-time updates; re-platform the Distributed Lock Service onto a strongly consistent backend; and build the self-serve tooling and recommendation engine that let customers describe a workload (QPS, TTL, payload size, latency profile) and get the right backend without talking to a human. You'll go deep on cache invalidation, replication, sharding, compaction, and failover, while shipping the guardrails, automation, and observability that keep this scale operable by a small team.

Requirements

6+ years of full-time experience designing, building, and operating distributed, stateful systems in production, at least 2 of which involved caching or key-value storage at meaningful scale.
Proficient in Go, or Java/Kotlin with deep expertise in concurrency, distributed systems, and production-grade backend services.
Hands-on experience with distributed caching technologies (Redis/Valkey, Memcached, or similar) and understand their failure modes: replication lag, failover, hot keys, and cache invalidation.
Understand distributed systems fundamentals: consistency models, sharding and partitioning, replication, and consensus, and can reason about their trade-offs from first principles.
Built or operated systems that require careful capacity planning and cost discipline at scale, and you default to right-sizing over over-provisioning.
Thrive in an execution-driven environment with a broad ownership area and a proven track record of shipping reliable infrastructure end to end.
Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring, and releasing software.

Nice To Haves

Hands-on experience with ElastiCache, Memcached, or Valkey in production.
Experience with KVRocks or RocksDB-family embedded storage engines (TiKV or similar), including compaction tuning and back-pressure handling.
Experience building or operating a distributed lock service.
Experience with Kubernetes and general cloud infrastructure operations.
Contributions to open-source caching, storage, or distributed systems projects.

Responsibilities

Own high-leverage caching and locking services with direct, measurable customer impact: cost, latency, and reliability at multi million QPS scale.
Build and scale Boulder, our KVRocks backed key-value store, including compaction, sharding, and domain isolation.
Re-platform the Distributed Lock Service onto a strongly consistent backend with sharding.
Contribute to the standardized smart caching client that bakes in failover, retry, and observability defaults so customers don't have to think about them.
Diagnose and resolve production issues that span cache invalidation storms, replication lag, hot shards, and noisy-neighbor contention, then turn each one into a durable guardrail rather than a one-off fix.
Collaborate closely with the teams that build on top of caching, including Taulu, ML Platform, and product engineering across DoorDash, Wolt, and Deliveroo.