RadixArk

Full Stack Engineer

Remote Palo Alto, CA
React Next.js TypeScript Python FastAPI Django Node.js API gRPC PostgreSQL Redis Docker Kubernetes Git Prometheus Grafana OpenTelemetry WebSockets
Description

Full stack engineer

Location: Palo Alto

Department: engineer

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.

RadixArk
RadixArk

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