Role Description We are looking for a Distributed Systems Engineer with experience in building high-performing, scalable, enterprise-grade applications. You will be responsible for: - Building API interfaces (for customers, UI team, etc.) - Building a high-performance queuing/storage engine - Collaborating with UI, connectivity, and DevOps teams to come up with elegant solutions to complex problems - Working in a polyglot environment where you can learn new languages and technologies whilst working with an enthusiastic team Responsibilities - Designing and developing high-volume, low-latency applications for mission-critical systems - Delivering high-availability and performance - Contributing in all phases of the development lifecycle - Writing well-designed, testable, efficient code - Evaluating and proposing improvements to existing systems Qualifications - 5+ years of industry experience - Experience building and shipping large-scale, reliable, highly distributed systems - Systems-level programming experience, especially in C, Go, Rust - Expertise in L2, L3, and/or L4 networking protocols - Good understanding of Linux networking and security - Experience building on top of Linux kernel networking primitives – netfilter, nftables, eBPF, tc, network namespaces, etc. - Experience with large-scale distributed data pipelines, from data structuring to efficient querying to data analysis - Experience of working with public cloud infrastructure providers (AWS/Azure/Google Cloud) - Understanding of Kubernetes concepts - Excellent debugging and optimization skills - Understanding at the protocol level, including the differences between what the specs say, and what actually happens on the Internet - Contributions to open source projects is a plus - Excited by the idea of optimizing complex solutions to general problems - Attention to detail and ability to solve complex customer problems - Own solutions end-to-end and drive the design, development, and deployment process - Able to work across teams and level common, sustainable solutions

• Lead the design and implementation of secure, fault-tolerant, and highly available cloud infrastructure on public cloud services. • Continuously improve system performance, identify bottlenecks, and deploy optimizations for smooth operation at scale for highly-trafficked services. • Lead the evolution of our Continuous Integration and Deployment pipelines in a multi-service environment, reducing complexity and increasing resilience. • Plan and execute timely infrastructure upgrades and changes using infrastructure-as-code to enable faster execution, improved scale, and increased cost efficiency. • Leverage tools like DataDog, Sentry, and others to monitor system infrastructure, configure alerts for anomalies, and proactively ensure system health. • Define, promote, and maintain runbooks, operating procedures, and system architecture diagrams. Uphold high standards of quality through rigorous testing and code reviews. • Act as a force multiplier by providing technical guidance, mentoring other engineers, and fostering a culture of engineering excellence. • Embrace a culture of flexibility and efficiency, moving fast to capture opportunities while wearing multiple hats in a startup environment

• Ship full-stack product features end-to-end across frontend, backend, and data • Build AI-powered experiences using LLMs, embeddings, and related techniques where they create real user value • Own delivery from scope/design through launch, monitoring, and iteration • Solve ambiguous, technically challenging problems with pragmatic, scalable solutions • Partner closely with product, design, and engineering to shape requirements and roadmap • Improve performance, reliability, and overall product quality at enterprise scale • Contribute to strong engineering culture through code review, tooling, and process improvements

• Build and maintain scalable backend systems and data pipelines that support audience segmentation and marketing attribution workflows • Partner with product managers, marketers, and engineers to deliver data solutions that support customer acquisition and conversion goals • Extend existing data infrastructure to support increasing data volumes, evolving business requirements, and new integrations • Contribute to data quality initiatives by implementing monitoring, validation, and guardrail mechanisms across critical datasets • Participate in technical discussions around architecture, access patterns, and platform scalability to support long-term platform growth