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Full stack engineer at RadixArk. . Location: Palo Alto. . . About The Role. . . . RadixArk is building the infrastructure layer for frontier AI systems — unified inference, training, and evaluation stacks powering next-generation LLM applications at scale. Our platform integrates high-performance model serving, RL pipelines, and large-scale distributed systems across GPUs, TPUs, and emerging accelerators. We work at the intersection of systems engineering, AI research, and developer experience. We are looking for a world-class Full Stack Engineer who thrives in high-ambiguity environments and wants to build foundational tools for the next decade of AI.. . . . . . Requirements. . . . Technical Excellence. . . . 4+ years of professional full stack engineering experience. . . . Based in Palo Alto, CA (Hybrid) / Remote (U.S.). . . . Deep experience in:. . . . Frontend:. React / Next.js / TypeScript. . . . Backend:. Python (FastAPI / Django) or Node.js. . . . RESTful and/or gRPC API design. . . . . . Strong understanding of distributed systems concepts. . . . Experience building systems that handle real-time streaming or high-throughput workloads. . . . Strong database design skills (Postgres, Redis, etc.). . . . Familiarity with containerized environments (Docker, Kubernetes). . . . Strong software engineering fundamentals: testing, CI/CD, version control, design reviews. . . .  . . Bonus (High Impact). . . . Experience building developer tools or infrastructure platforms. . . . Experience in ML infrastructure, model serving, or AI tooling. . . . Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry). . . . Experience with WebSockets or streaming architectures. . . . Performance optimization at scale. . . . Experience building internal platforms used by engineers. . . . . . . . Responsibilities. . . . You will own end-to-end product surfaces across our developer platform:. . . . Design and implement high-performance web applications for AI infrastructure tooling. . . . Build scalable backend systems that interact with distributed inference and training services. . . . Architect APIs and service layers that serve enterprise and research customers. . . . Develop observability dashboards, experiment tracking UIs, and performance analytics tools. . . . Optimize real-time streaming interfaces for model inference workflows. . . . Work closely with ML engineers and infra teams to expose complex systems through intuitive product surfaces. . . . Lead architectural decisions for frontend-backend communication, state management, and performance tuning. . . . Ship production-grade features in fast iteration cycles. . . . You will not just “write UI.”. You will build the control plane for frontier AI systems.. . Your work will directly power:. . . . Large-scale LLM inference systems. . . . Reinforcement learning training platforms. . . . Evaluation and experimentation frameworks. . . . Developer-facing AI infrastructure products. . . . This is not CRUD dashboard engineering.. This is building the operating system for AI builders.. . . . . . About RadixArk. . . . RadixArk is building the infrastructure layer for frontier AI systems — unified inference, training, and evaluation stacks powering next-generation LLM applications at scale.. . Our platform integrates high-performance model serving, RL pipelines, and large-scale distributed systems across GPUs, TPUs, and emerging accelerators. We work at the intersection of systems engineering, AI research, and developer experience.. . . . . . Compensation. . . . . . Competitive base salary. . . . Meaningful equity ownership. . . . Full benefits. . . . Access to top-tier AI tooling (enterprise Claude, Codex, etc.). . . . Work alongside world-class AI systems engineers. . . . . . . . Equal Opportunity. . . . . . Competitive salary and equity package.. . . . Work with a world-class team from xAI, Google, and leading research labs.. . . . Directly impact the future of open AI infrastructure.. . The most compelling perk in Silicon Valley isn’t 401(k) matching.. It’s working on systems that define the next computing paradigm.. . If you want to build the infrastructure layer behind frontier AI — and ship fast — we want to talk.. . . .