xai

Software Engineer - Internal Tools

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At a Glance

Location
Palo Alto, California, United States
Compensation
text here Annual Salary Range $180,000 - $440,000 USD Benefits Base salary is j
Posted
2026-03-06T18:53:29-05:00

Key Requirements

Required Skills

Machine LearningReactRustTypeScript

Requirements

Experience building high-performance backend systems in dynamic, fast-paced environments - as a tech lead, former founder, etc.

Expertise in designing scalable distributed systems and APIs with a compiled language like Rust or C++.

Experience optimizing data pipelines for machine learning workloads or real-time applications.

Familiarity with frontend technologies (e.g., TypeScript, React) to collaborate seamlessly with cross-functional teams.Enter text here

Compensation & Benefits

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

xAI is an equal opportunity employer. For details on data processing, view our

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Responsibilities

The xAI Tooling team (Starfleet) is looking for a backend engineer who will be responsible for designing, developing, and maintaining robust, scalable backend systems that empower our researchers, engineers, and product teams to build, experiment with, and deploy cutting-edge AI models and applications more effectively.

In this role, you will own high-impact tooling projects including internal APIs, data pipelines, orchestration layers, and tooling platforms that streamline workflows for training, inference, evaluation, and deployment.

If you're excited to create the foundational tools that make building the world's most powerful AI systems faster and more efficient, this role offers the chance to have outsized impact at the frontier of AI development.

Design and build robust, scalable backend systems to power our AI-driven tools and platforms.

Develop APIs and distributed systems that handle high-throughput data processing for model training and evaluation.

Create secure, reliable pipelines to support innovative human data generation and agentic workflows.