Primary record

Staff Software Engineer, Full Stack - Gen AI

Scale AI Indexed employerNew York, NY; San Francisco, CA; Seattle, WA; New York, NY · San Francisco, California, United States
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Workplace

On-site

Employment

Internship

Published

Aug 11, 2026

Closes

No date supplied

The role

Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

This is a horizontal, high-impact L6 Staff Fullstack Engineer & Architect position reporting directly to the Director of Contributor Engineering.

Instead of being tied to a single domain, your scope is spread across all Contributor (CB) teams (including Allocation, Growth, Trust & Safety, Pay, and Allocations). Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale.

You will act as an organizational architect and tech lead, dynamically embedding yourself into the highest-priority projects across the org to guarantee execution, unblock teams, and successfully ship mission-critical initiatives. Concurrently, you will lead the long-term technical evolution of our stack, transforming the core architecture to ensure it is highly sustainable, scalable, and fundamentally AI-native.

You will:

• Deploy flexibly into critical, fast-moving product initiatives across the CB organization

• Lead the architectural overhaul of our platform infrastructure, making it highly sustainable, robust, and optimized for deep integration with LLMs and foundation models.

• Lead architecture decisions for scalability, reliability, and performance

• Mentor and uplevel engineers across the team

• Partner with product and leader

Requirements

Department: Gen AI Engineering