Job Description

About HighLevel:

HighLevel is an AI powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 2 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 micro-services, and supports over 1 million hostnames.

Our People

With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.

Our Impact

As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 2 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.

Role Summary:

We're hiring a Staff Engineer - Backend (Data Systems) to own and evolve the data backbone that powers messaging at scale inside HighLevel's Conversations platform.
You'll design, operate, and scale systems that handle billions of documents across MongoDB, Firestore, Redis, and ElasticSearch -- with reliability, predictability, and engineering clarity as non-negotiables.
This is a hands-on IC role -- you'll code, design, review, and guide. You'll set the standard for how we think about databases, APIs, and engineering craft.
The goal: make our data systems boring in the best possible way -- predictable, fast, and easy to trust.
Your first project will be to re-architect and scale ElasticSearch to handle billions of documents efficiently while setting best practices for schema design, observability, and testing discipline across the org.

Team & Project Overview:

You'll join the Conversations team -- the core communication platform at HighLevel that powers SMS, Email, WhatsApp, and DMs for millions of users.
The system processes 2B+ messages monthly, spanning 50+ workloads and thousands of pods across GCP (GKE, Pub/Sub, Cloud Tasks).
The data stack includes MongoDB, Firestore, Redis, ElasticSearch, and ClickHouse -- distributed, high-volume, and mission-critical.
This role sits at the intersection of data architecture and engineering culture -- scaling systems while shaping how engineers design, test, and reason about them.

Responsibilities:

Database architecture:

Redesign and optimize data models, queries, and indexing strategies across MongoDB, Firestore, and ElasticSearch

Search at scale:

Own ElasticSearch reliability -- ingestion, indexing, shard strategy, and query performance for billions of documents

Reliability & performance:

Eliminate bottlenecks, improve replication health, and enforce predictable query and index latency

System design:

Define data flow and integration boundaries between storage, cache, and APIs with clear contracts and fault isolation

Observability:

Build visibility into every data path -- metrics, traces, slow query logs, replication lag, and cluster health dashboards

Testing & quality:

Make testing non-negotiable -- enforce unit, integration, and load testing standards across all backend modules

Engineering culture:

Drive RFCs, ADRs, and design reviews that push clarity and precision. Codify patterns that make good engineering repeatable

Hands-on leadership:

Write code, design systems, and debug production issues. Lead by technical example, not by delegation

Mentorship & influence:

Level up engineers around you -- reviews that teach, feedback that sticks, and systems that outlive individuals

Requirements:

8+ years of backend engineering experience with deep database expertise Proven success with ElasticSearch, MongoDB, or Firestore at massive scale Strong understanding of indexing, query optimization, caching, and consistency models Expert in Node.js (TypeScript) and comfortable designing scalable microservices Cloud experience with GCP (GKE, Pub/Sub, Cloud Tasks) or similar distributed infra Practical knowledge of observability: Grafana, Kibana, OpenTelemetry Passion for code quality and process: testing discipline, documentation, and design rigor A track record of shaping team culture -- setting standards through RFCs, ADRs, and clear technical writing No tolerance for regressions, unclear ownership, or untested systems

Nice to Have:

Experience with ElasticSearch cluster management, multi-tenant indexing, or lifecycle policies Familiarity with ClickHouse or other OLAP systems for analytics Background in event-driven systems, data pipelines, or message brokers Contributions to open-source or public technical writing on database performance or systems design

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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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.