HighLevel - Staff Engineer
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 • 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
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
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