Staff Engineer - Platform Engineering

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: Responsibilities:

Architect, develop, and maintain reusable frameworks, SDKs, and core platform services using Node.js and GoLang

Build scalable, cloud-native solutions leveraging Google Cloud Platform (GCP)

Design and optimize systems that efficiently handle large-scale data and high-throughput workloads

Contribute to high-performance service architectures capable of handling massive scale with strong reliability and observability standards

Lead technical design reviews, establish engineering best practices, and mentor senior engineers across teams

Drive architectural decisions for scalability, performance, security, and maintainability

Partner cross-functionally with product, infrastructure, and engineering teams to deliver reliable platform capabilities

Improve developer productivity by building internal tooling, shared libraries, and scalable engineering foundations

Lead initiatives that leverage AI effectively across engineering workflows, including code generation, testing, developer tooling, incident analysis, and SDLC automation

Build and evolve systems, platforms, and engineering processes that improve SDLC efficiency, release velocity, reliability, and developer experience

Take ownership of critical platform initiatives from architecture through production operations

Requirements:

9+ years of software engineering experience with demonstrated success building distributed systems or large-scale backend services

Hands-on experience designing, optimizing, and scaling large-scale backend systems and data-intensive applications

Strong understanding of distributed systems, microservices, APIs, CI/CD pipelines, and observability frameworks

Experience leveraging AI-assisted engineering workflows and building systems/processes that improve SDLC effectiveness and engineering productivity

Proven ability to lead technically, navigate ambiguity, and deliver impactful engineering outcomes

Experience operating systems at high scale with a strong focus on performance, reliability, and resiliency

Strong problem-solving skills with the ability to simplify complex technical challenges

Nice to Have:

Experience building internal platforms, frameworks, or developer tooling used across multiple teams

Strong expertise in Node.js/GoLang and cloud infrastructure, preferably GCP

Familiarity with Kubernetes, service mesh technologies, and infrastructure automation

Experience in high-traffic SaaS environments with a focus on scalability and resilience

Exposure to event-driven architectures, streaming systems, or large-scale data platforms

Experience evaluating or implementing AI-enabled developer platforms, coding assistants, or SDLC automation systems