We are looking for a frontend-focused full-stack engineer to help build AI-powered applications that redefine enterprise workflows and push the boundaries of interactive AI. This role is ideal for someone who thrives in a fast-paced environment, enjoys working on a diverse set of projects, and has a passion for crafting high-quality, intuitive user experiences.
What you'll do
At Scale, you'll work on a mix of cutting-edge customer-facing AI applications and internal SaaS products. Our engineering team powers projects like TIME's Person of the Year AI experience, where our AI technology helped shape one of the most iconic features in media. You'll also contribute to Scale's GenAI Platform (SGP), a powerful system that enables businesses to build and deploy AI agents at scale.
- Build and enhance user-facing AI applications for major enterprise customers, including high-profile media and Fortune 500 companies
- Develop and refine features for Scale's GenAI Platform, empowering businesses to build, deploy, and manage AI-driven agents
- Design, build, and optimize polished, high-performance UIs using Next.js, React, TypeScript, and Tailwind
- Work closely with product managers, designers, and AI/ML teams to create seamless, intuitive, and impactful user experiences
- Integrate frontend applications with backend services, working with APIs, authentication systems, and cloud-based infrastructure
- Ship features at a rapid pace while maintaining a high level of code quality, performance, and accessibility
What you need
- 5+ years of experience developing frontend or fullstack applications in a modern tech stack
- Strong proficiency in Next.js, React, TypeScript, and Tailwind, with an eye for building polished, user-friendly interfaces
- Experience working on high-visibility, customer-facing applications and making trade-offs between speed and quality in fast-paced environments
- A passion for AI and experience working on interactive AI applications, agent-based systems, or data-rich web platforms
- Familiarity with backend technologies such as FastAPI, PostgreSQL, GraphQL, and cloud infrastructure like AWS, Azure, or GCP
- A track record of collaborating cross-functionally with design, product, and ML teams to bring AI-powered applications to life
