Staff Engineer – Distributed Data Systems & Infrastructure

About HighLevel:
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.

About the Role:
We are looking for an exceptional Staff Engineer to shape the architecture and evolution of our data infrastructure as we scale. Our engineering ecosystem operates multiple database technologies, handles large volumes of data and traffic, and supports a growing number of services and engineering teams. We need a strong individual contributor who has built and scaled distributed data systems, understands database technologies at a fundamental level, and can solve complex infrastructure challenges across multiple engineering teams. This role goes beyond operating existing databases. You will design systems, build infrastructure capabilities, challenge architectural limitations, and drive technical initiatives that improve scalability, reliability, performance, and infrastructure economics.

What You'll Do:
Architect for scale: Design and evolve distributed data architectures capable of supporting significant growth in traffic, data volume, and engineering complexity. Build infrastructure platforms: Develop reusable infrastructure components, frameworks, and platform capabilities that enable engineering teams to build scalable systems. Drive architectural evolution: Identify fundamental limitations in existing systems and lead large-scale initiatives involving data distribution, sharding, replication, migrations, and architectural modernization. Shape technical strategy: Influence database technology choices, architectural patterns, and long-term infrastructure direction across the company. Improve infrastructure economics: Lead engineering initiatives that materially improve scalability, resource efficiency, and infrastructure costs. Engineer for reliability: Design systems that remain available and resilient under high throughput, infrastructure failures, and changing workload patterns. Create organizational leverage: Establish engineering standards and reusable solutions that eliminate recurring problems across teams. Lead through technical influence: Work with senior engineers and engineering leadership to turn ambiguous, company-level challenges into executable technical programs.

What We're Looking For:
9+ years of strong software engineering experience, including significant hands-on experience designing and building distributed systems, backend infrastructure, or large-scale data platforms, with demonstrated Staff-level technical impact. Strong software engineering background with experience designing and building production infrastructure, not only operating or administering it. Experience architecting systems handling multi-terabyte datasets and 30K–50K+ operations per second, or comparable large-scale distributed workloads. Deep understanding of distributed systems concepts, including partitioning, sharding, replication, consistency, concurrency, fault tolerance, and data distribution. Strong hands-on experience with both relational and NoSQL database architectures, including their design principles, scalability characteristics, and trade-offs. Experience leading complex architectural initiatives involving multiple systems and engineering teams. Ability to identify systemic technical problems and design solutions that improve infrastructure across the organization. Strong technical judgment, ownership, and the ability to influence architectural decisions without formal authority.

Tech Experience:
We value engineering depth and architectural understanding over familiarity with a long list of technologies. Strong experience with relational databases such as MySQL or PostgreSQL, combined with experience in one or more distributed database technologies such as MongoDB, Cassandra, DynamoDB, or similar systems, is highly relevant. Experience with distributed SQL, search infrastructure, analytical databases, or other large-scale storage systems is an advantage. We do not expect expertise in any particular combination of database products. What matters is the ability to understand their internals, evaluate trade-offs, and design scalable infrastructure around them.

What Makes Someone Successful in This Role:
You have previously taken ownership of challenging infrastructure problems where the solution required more than improving an individual service or database. You have designed or significantly evolved distributed architectures, built infrastructure adopted by multiple teams, led complex technical transformations, or enabled systems to operate at substantially greater scale. You are equally comfortable discussing database internals, distributed systems trade-offs, and long-term architecture as you are working with engineers to turn those decisions into production systems. Your impact is measured by the systems you enable, the architectural problems you eliminate, and the engineering capabilities you leave behind.

EEO Statement:
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