Staff Engineer - Backend

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 a Staff Engineer – Backend to help design, build, and evolve the  systems powering HighLevel’s CRM platform. This is a senior individual contributor role for an engineer who can solve complex backend and distributed systems problems, influence architecture across teams, and raise the engineering bar across the organization. 

You will work on systems handling high-volume APIs, asynchronous processing, large datasets, search and indexing, event-driven workflows, and business-critical operations at scale. This role requires someone who can move comfortably between architecture and implementation. You should be able to investigate a production bottleneck, design a scalable solution, challenge existing architectural assumptions, and work hands-on with engineers to take that solution to production.

What You ll Do

Design and evolve highly scalable, reliable backend systems and services

Lead architecture for complex and cross-team backend initiatives

Design APIs, data models, event-driven workflows, and service boundaries

Build systems capable of handling high-throughput requests and large-scale datasets

Design asynchronous processing using queues, events, streams, and background workers

Make architectural decisions around relational databases, NoSQL databases, search systems, caching, and messaging infrastructure

Identify performance bottlenecks across applications, databases, queues, and infrastructure

Improve API latency, throughput, resource utilization, and system scalability

Design systems for graceful degradation, retries, idempotency, failure recovery, and fault tolerance

Establish patterns for data consistency and distributed workflows across services

Lead database and data-access optimization initiatives

Design effective caching, indexing, partitioning, sharding, and data-retention strategies

Improve observability through metrics, logs, tracing, dashboards, and actionable alerts

Lead investigations into complex production incidents and drive permanent corrective actions

Define engineering standards around reliability, scalability, testing, security, and maintainability

Review architecture proposals and critical code changes across teams

Identify systemic technical debt and drive pragmatic modernization initiatives

Partner with Product and Engineering leadership to make technical trade-offs based on business requirements

Mentor senior engineers and develop stronger technical ownership across teams

Remain hands-on and contribute code to critical systems and initiatives

Minimum Qualifications

8+ years of software engineering experience , with significant experience building backend systems at scale

Strong proficiency in at least one backend language such as Node.js/TypeScript, Go, Java, or similar

Strong understanding of distributed systems and microservice architecture

Deep understanding of API design and service-to-service communication

Strong knowledge of relational and NoSQL database systems

Experience designing systems involving large datasets and high request volumes

Strong understanding of concurrency, asynchronous processing, queues, and event-driven architectures

Experience with caching and distributed caching strategies

Strong understanding of database indexing, query optimization, transactions, and data consistency

Experience designing reliable systems with retries, idempotency, timeouts, rate limiting, and failure recovery

Strong understanding of scalability, availability, consistency, and performance trade-offs

Experience diagnosing complex production issues using metrics, logs, and distributed tracing

Strong system design and architectural decision-making skills

Demonstrated ability to lead technically complex initiatives involving multiple engineers or teamsPreferred Qualifications

Strong experience with Node.js / TypeScript and Go

Experience operating distributed systems at significant scale

Experience with Elasticsearch / OpenSearch

Experience with PostgreSQL, MySQL, MongoDB, Firestore, or similar databases

Experience with Kafka, Pub/Sub, RabbitMQ, SQS, or similar messaging systems

Experience with Redis and distributed caching

Experience designing search, indexing, aggregation, and reporting systems

Experience with high-volume event processing and data pipelines

Experience with Kubernetes and cloud-native infrastructure

Experience with AWS, GCP, or similar cloud platforms

Experience with observability platforms such as Grafana, Prometheus, OpenTelemetry, or similar tooling

Experience designing multi-tenant SaaS platforms

Experience with CRM, workflow automation, task management, messaging, or similar products

Experience performing large-scale data migrations without significant customer Impact

Tech Stack

Backend: Node.js, TypeScript, Go

Databases & Search: MySQL, MongoDB, Firestore, Elasticsearch/OpenSearch

Caching: Redis

Messaging & Events: Kafka, Pub/Sub

Architecture: Microservices, REST APIs, Event-Driven Systems

Infrastructure: Kubernetes, GCP

Observability: Metrics, Logs, Distributed Tracing and Alerting

What Success Looks Like

A successful Staff Engineer:

Designs systems that remain reliable as traffic and data volume grow significantly

Solves architectural problems that affect multiple services and engineering teams

Identifies scalability and reliability risks before they become production incidents

Improves latency, throughput, availability, and infrastructure efficiency

Makes strong technical decisions around data storage, caching, messaging, and service architecture

Simplifies complex systems rather than introducing unnecessary abstractions

Creates reusable architectural patterns that improve engineering velocity across teams

Leads ambiguous technical initiatives from problem definition through production

Raises the quality of system design and technical decision-making across the organization

Improves operational excellence through better observability, incident prevention, and failure recovery

Mentors engineers to independently solve increasingly complex systems problems

Remains hands-on and capable of going deep into production systems when required

What We Look For

We are looking for engineers who think about systems beyond the happy path.

A Staff Engineer should naturally ask:

What happens when this system handles 10x the current traffic?

What happens when a dependency becomes slow or unavailable?

How does this behave when millions of events arrive within a short period?

What are our consistency guarantees, and where can we tolerate eventual consistency?

How do we prevent duplicate processing and make operations idempotent?

Is the database the bottleneck, or are we solving the problem at the wrong layer?

Should this data live in a transactional database, search engine, cache, or event stream?

How do we migrate this architecture without disrupting existing customers?

How will we observe this system in production and know when it is degrading?

Can we solve this once at the platform level instead of every team solving it independently

The Staff Engineer role is not defined by writing the most code. It is defined by identifying the highest-leverage technical problems, making strong architectural decisions, solving the hardest parts, and enabling engineering teams to build reliable systems faster.

Why Join Us

Build backend systems operating at significant global scale

Solve challenging distributed systems and data architecture problems

Influence architecture across multiple products and engineering teams

Work with high-volume APIs, event streams, databases, search systems, and distributed infrastructure

Drive improvements in scalability, reliability, performance, and engineering efficiency

Remain deeply technical without moving into people management

Work in a fast-moving engineering environment with significant autonomy and Ownership

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