Senior SDE - Platform

Design and build the platform components Workflows and Conversations run on, queueing pipelines, storage access layers, caching strategies, rate limiters, schedulers

Own your components end to end: architecture, design docs, code, tests, rollout, dashboards, and production health

Go deep on data stores at scale, schema and index design, sharding strategies, replication behavior, and migrations on live systems with billions of records

Work close to the infrastructure: GKE autoscaling, resource tuning, Pub/Sub and Cloud Tasks topologies, and the capacity planning that keeps headroom ahead of growth

Spot gaps in your systems before production does, missing idempotency, unbounded queues, cache stampedes, hot shards, and drive the fixes

Debug the incidents that cross layers, where the answer isn't in one service's logs but in how the pieces interact

Write design docs and RCAs that make the platform's behavior legible to 80+ engineers building on it

Runtime: Node.js (TypeScript), Go, on GKE

Messaging & async: GCP Pub/Sub, Cloud Tasks, Redis

Storage: MongoDB, Firestore, ClickHouse, ElasticSearch

Observability: metrics, tracing, and alerting you'll help make sharper

4+ years of backend engineering experience, with deep hands-on work in Node.js and/or Go

Strong systems understanding across the stack, application, database, and infrastructure, proven on high-throughput production systems

Deep experience with queueing and async processing, Pub/Sub, Kafka, RabbitMQ, Cloud Tasks, or similar, delivery semantics, ordering, backpressure, idempotency

Database depth beyond CRUD, indexing strategies, sharding, replication, query performance, and safe migrations on SQL or NoSQL stores at scale

Hands-on with Redis or other in-memory stores, caching patterns, data structures, and their failure modes

Production experience with cloud infrastructure, Kubernetes, autoscaling, resource limits, and how they behave under pressure (GCP preferred)

You write clear design docs and rigorous test cases as a habit, not on request

Champion of AI-assisted engineering, you make agents produce accurate, production-quality code, fast

You understand systems in depth, not just the API surface, but what happens under load, at the tail, when the network partitions

You've taken real production hits, a migration gone sideways, a queue that wouldn't drain, a database that fell over, and each one made your designs better

You're the engineer teammates pull in when the bug crosses layers, app, database, infra, because you can hold all three in your head

You write design docs people actually read, clear trade-offs, honest risks, a real recommendation

You treat capacity and failure modes as design inputs, not afterthoughts

When production breaks, your first instinct is curiosity, not panic

You've operated systems at comparable scale, billions of events, thousands of instances

Experience with ClickHouse, ElasticSearch, or Firestore in production

You've done platform work before, the unglamorous layers everyone depends on and nobody notices until they fail