Senior Software Engineer

Senior Platform Engineer – AI Infrastructure$200-$300k base + Equity (depending on leveling)We’re building the infrastructure platform powering real-time AI workloads across distributed GPU environments.This is not a traditional DevOps role focused purely on CI/CD pipelines or infrastructure maintenance. We’re looking for a senior platform engineer who enjoys building and evolving complex infrastructure systems - someone who can operate across Kubernetes, distributed systems, networking, observability, and deployment architecture in a highly ambiguous, fast-moving environment.You’ll help shape the foundational infrastructure layer for a production AI platform running across multiple regions, cloud providers, and GPU environments.What You’ll Work OnBuild and evolve multi-region Kubernetes infrastructure across AWS and GPU cloud providersDesign and improve internal platform systems that enable engineering and ML teams to deploy reliably at scaleOwn infrastructure-as-code across environments using Terraform and modern GitOps workflowsImprove deployment architecture, cluster scalability, reliability, and operational efficiencyWork on observability across distributed systems using metrics, logs, traces, and profilingPartner closely with ML and backend engineers on model serving infrastructure, workload optimization, and platform performanceImprove networking and connectivity across distributed environments, including ingress, gateways, load balancing, and cross-region trafficHelp shape security, secrets management, access controls, and infrastructure compliance practicesContribute to developer experience through tooling, automation, and infrastructure abstractionsWhat We’re Looking ForWe’re looking for engineers who think in systems, not silos.You’ll likely have experience across several of the following:Operating Kubernetes in production at meaningful scaleBuilding infrastructure platforms rather than simply maintaining deploymentsInfrastructure-as-code using Terraform, Pulumi, or similar toolingGitOps workflows using ArgoCD, FluxCD, Helm, or KustomizeDistributed infrastructure and multi-region environmentsObservability tooling such as Prometheus, Grafana, OpenTelemetry, or similarStrong infrastructure fundamentals across networking, reliability, and securityExperience coding in Go or Python where needed for tooling, automation, or infrastructure systemsWorking in startup or high-growth environments with significant ownership and ambiguityNice to HaveGPU infrastructure or ML platform exposureExperience with AI inference or model-serving systemsReal-time networking or media infrastructure experienceExposure to GPU cloud providers such as CoreWeave, Crusoe, Lambda, or similarFinOps or infrastructure cost optimization experienceWhat This Role Is NotThis is not a narrowly scoped DevOps or support engineering position.We’re not looking for someone focused solely on maintaining CI/CD pipelines or reacting to tickets. We’re looking for engineers who enjoy designing systems, improving infrastructure foundations, and solving complex operational problems across the platform stack.Why JoinYou’ll have significant ownership over foundational infrastructure decisions in a company scaling real-world AI workloads in production.This role is ideal for engineers who enjoy:solving ambiguous infrastructure problems,building scalable internal platforms,operating distributed systems,and working close to the intersection of infrastructure, performance, and developer enablement.