Senior Software Engineer (Infrastructure)

Accountabilities: Design, build, and maintain the application code responsible for managing persistent, always-on cloud environments for individual customers. Own the lifecycle management of virtual machines, container updates, background jobs, queues, observability, and security mechanisms. Develop scalable backend services, APIs, and infrastructure abstractions that enable product engineers to build and deploy new capabilities efficiently. Design and implement reliable distributed systems, including messaging queues, distributed locks, background tasks, and service bus mechanisms. Scale infrastructure from hundreds of customer environments to several thousand while maintaining high availability, performance, and reliability. Develop and improve Infrastructure-as-Code patterns using Pulumi or comparable technologies, establishing reusable standards and provisioning practices. Work with Docker, Kubernetes, cloud platforms, Linux systems, networking, storage, and permissions to support complex production workloads. Diagnose and resolve technical issues across application and infrastructure layers, identifying bottlenecks and implementing long-term improvements. Establish robust monitoring, observability, and security practices across customer environments. Partner with platform and product engineering teams to define technical architecture, establish engineering standards, and accelerate product development. Take end-to-end ownership of technical initiatives, from architecture and implementation through deployment, monitoring, and production debugging. Requirements 6–12 years of professional software engineering experience, particularly in backend development and core infrastructure engineering. Previous experience building or contributing to core infrastructure within an AI-native Series A–C startup. This is an essential requirement. Currently hands-on with production application development, with a strong preference for backend-focused engineers rather than traditional DevOps or SRE profiles. Proven experience taking ownership of infrastructure components such as virtual machines, queues, containers, and persistent cloud environments. Strong backend engineering skills and the ability to design, implement, deploy, and maintain production systems independently. Expertise in Infrastructure-as-Code tools such as Pulumi, Terraform, or AWS CDK. Practical experience with Docker, Kubernetes, or comparable container orchestration technologies. Deep knowledge of cloud infrastructure across Azure, AWS, or Google Cloud Platform (GCP). Strong understanding of Linux systems, networking, persistent storage, permissions, and runtime debugging. Experience designing distributed systems, asynchronous processing, background tasks, messaging queues, and reliable service architectures. Ability to build application code that controls and manages infrastructure, rather than relying exclusively on configuration and operational tooling. Experience designing APIs, backend services, and reusable abstractions for other engineering teams. Strong understanding of scalability, infrastructure reliability, performance optimization, and production system operations. Familiarity with AI-driven products and enthusiasm for working in an AI-forward engineering environment. Comfortable making architectural decisions and delivering solutions in ambiguous, fast-paced startup environments. Excellent communication skills in English, with the ability to explain complex technical concepts clearly. Strong ownership, accountability, collaboration, and problem-solving skills, combined with a bias toward execution and high engineering standards. Nice to Have: Experience managing isolated, per-customer cloud environments at scale. Previous work involving persistent cloud workloads, virtual machine lifecycle management, or container orchestration. Experience with Microsoft Azure, AWS, or GCP. Founder, Founding Engineer, or early-stage startup experience. Familiarity with TypeScript and Node.js. Hands-on experience with Pulumi, Docker, Kubernetes, MongoDB, Elasticsearch, and Linux. Experience implementing observability and monitoring solutions using Prometheus, Grafana, or Datadog. Benefits Competitive annual salary: $250,000–$325,000. Potential compensation flexibility up to $500,000 for exceptional candidates, depending on experience and role scope. Competitive equity package. Fully remote working environment. Location flexibility for candidates based in Canada, the United States, or Western Europe. Full-time employment opportunity. High level of technical autonomy and ownership over critical infrastructure systems. Opportunity to influence foundational architecture and engineering decisions. Direct collaboration with a small, highly skilled engineering team. Opportunity to work at the intersection of artificial intelligence, backend engineering, and cloud infrastructure. Exposure to complex technical challenges while helping scale an innovative AI platform from hundreds to thousands of customer environments.