HighLevel is an AI-powered business operating system that gives agencies, entrepreneurs and SMBs the infrastructure to build, automate and scale. Today, HighLevel supports SMBs across 150+ countries, fueling community-driven growth rooted in real customer outcomes.
To date, businesses operating on HighLevel have generated over $7 billion in ecosystem value, demonstrating the impact of shared infrastructure at scale. By centralizing conversations, automation and intelligence into one system, we help businesses move faster, reduce complexity and execute efficiently.
Behind the platform, HighLevel powers more than 4 billion API hits and 2.5 billion message events daily. With 250 terabytes of distributed data, 250+ microservices and over 1 million domain names supported, our architecture is built for performance, resilience and long-term scalability.
Our people
With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home.
Our impact
Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We’re proud to be a part of that.
Learn more about us on our YouTube Channel or Blog Posts
What are we hiring for?
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.
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
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
The terrain:
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.
That means making agents do real work: producing code that's accurate, tested, and slop-free, fast. On platform code, the bar is higher, not lower: a sloppy merge here doesn't break a feature, it breaks the floor everything stands on. You review AI output with that in mind, and you ship at a pace engineers without this skill can't match.
What you're built for
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
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
EEO Statement:
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
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