Founding Engineer - Full-stack

As a Full Stack Engineer at the company, you will be responsible for building the core platform that supports various AI workflows. You will collaborate with product and business teams to develop systems for expert onboarding, workflow management, annotation, quality review, reporting, and AI-assisted operations. Key Responsibilities: - Build and scale onboarding, qualification, task allocation, and review workflows. - Develop modern web applications and internal platforms. - Create dashboards for quality, productivity, project tracking, and reporting. - Build backend services for authentication, permissions, workflow orchestration, and audit logging. - Integrate AI-powered features and automation into core workflows. - Own features end-to-end from design to deployment. Qualification Required: - 2-4 years of software engineering experience. - Strong proficiency in: - Frontend: React.js, Next.js, TypeScript - Backend: Node.js (Python experience is also acceptable) - Experience building and consuming APIs. - Strong understanding of databases, authentication, system design, and scalable architectures. - Ability to write clean, maintainable, production-grade code. - High ownership and problem-solving mindset. The company is focused on building data and human-in-the-loop infrastructure for frontier AI companies. They cover expert annotation, model evaluation, RLHF/SFT, voice, video, coding, education, medical, and multilingual AI workflows. If you have AI experience, it is a plus. Hands-on experience in building AI-powered products/features or working with LLMs is required. Regular use of AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, etc., is expected. The ability to accelerate development cycles using AI while maintaining engineering quality is essential. Preferred experience includes working with workflow tools, internal platforms, marketplaces, dashboards, or B2B SaaS products. Exposure to annotation platforms, AI evaluation systems, RLHF/SFT pipelines, or human-in-the-loop workflows is beneficial. Knowledge of multimodal AI systems (text, code, audio, video) will be advantageous. As a Full Stack Engineer at the company, you will be responsible for building the core platform that supports various AI workflows. You will collaborate with product and business teams to develop systems for expert onboarding, workflow management, annotation, quality review, reporting, and AI-assisted operations. Key Responsibilities: - Build and scale onboarding, qualification, task allocation, and review workflows. - Develop modern web applications and internal platforms. - Create dashboards for quality, productivity, project tracking, and reporting. - Build backend services for authentication, permissions, workflow orchestration, and audit logging. - Integrate AI-powered features and automation into core workflows. - Own features end-to-end from design to deployment. Qualification Required: - 2-4 years of software engineering experience. - Strong proficiency in: - Frontend: React.js, Next.js, TypeScript - Backend: Node.js (Python experience is also acceptable) - Experience building and consuming APIs. - Strong understanding of databases, authentication, system design, and scalable architectures. - Ability to write clean, maintainable, production-grade code. - High ownership and problem-solving mindset. The company is focused on building data and human-in-the-loop infrastructure for frontier AI companies. They cover expert annotation, model evaluation, RLHF/SFT, voice, video, coding, education, medical, and multilingual AI workflows. If you have AI experience, it is a plus. Hands-on experience in building AI-powered products/features or working with LLMs is required. Regular use of AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf, etc., is expected. The ability to accelerate development cycles using AI while maintaining engineering quality is essential. Preferred experience includes working with workflow tools, internal platforms, marketplaces, dashboards, or B2B SaaS products. Exposure to annotation platforms, AI evaluation systems, RLHF/SFT pipelines, or human-in-the-loop workflows is beneficial. Knowledge of multimodal AI systems (text, code, audio, video) will be advantageous.