Senior SDE - Platform

Job Summary

The platform underneath our two biggest systems.

Workflows executes 21.5 billion automation actions a month from 3.1 billion enrollments. Conversations moves 2.6 billion messages in the same window. Together they run on thousands of pods, across 50+ kinds of deployments, on top of multiple database engines, GCP Pub/Sub, Cloud Tasks, and Redis, with traffic peaking above 28,000 requests per second and growing double-digit percent every month.

Product engineers build the features. This role owns what the features stand on, the queues, the storage layers, the caching, the infrastructure, and makes sure it holds when the growth curve does what our growth curve does.

We're not looking for someone who knows one layer. We're looking for the engineer who understands the whole vertical: how a query plan behaves at 1.5 TB of indexes, why a pod eviction turned into a message backlog, what a Redis failover actually does to the request path. Databases, infra, cloud, you see through all of it.

Team System Overview

The Conversations organization powers multi-channel communication across SMS, Email, WhatsApp, and DMs - handling over 2B messages each month. The Threads Composer team owns the inbox and composer surfaces, and the backend services that deliver and store those interactions. You'll work across Node.js microservices, GCP-based infra (GKE, Pub/Sub, Cloud Tasks), and MongoDB/Firestore storage layers, ensuring every message and UI state stays consistent, fast, and recoverable.

Responsibilities

• 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 isnt in one services logs but in how the pieces interact
• Write design docs and RCAs that make the platforms behavior legible to 80+ engineers building on it

The terrain

• 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 youll help make sharper

Requirements

• 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

On AI

We're past the debate. AI is part of how we build, and we expect you to be better at it than most.

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