[Hiring] Senior SDE - Platform @HighLevel

Role Description

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.

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 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.

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 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.

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.

Bonus Points

• 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.