Architect and build the AI foundations platform that enables teams to integrate AI, LLMs, and generative capabilities into product experiences at scale.
Design and develop shared backend services, APIs, orchestration layers, and platform components that support AI-powered workflows across multiple teams and applications.
Work directly with AI/LLM technologies to support intelligent content workflows, generation pipelines, moderation and curation systems, and productivity enhancing product experiences.
Build robust server-side systems using Node.js, Java, or similar technologies, with a strong focus on scalability, reliability, performance, and maintainability.
Define and scale engineering best practices for AI development, including service design, evaluation workflows, observability, operational readiness, and production quality standards.
Develop systems that support distributed architectures, real-time collaboration, and multimedia-rich experiences, especially where AI capabilities are deeply embedded in customer-facing workflows.
Partner across teams to increase adoption of AI platform capabilities, reusable abstractions, and engineering standards that accelerate delivery and improve consistency.
Own projects end-to-end — from design and prototyping through implementation, testing, delivery, monitoring, and continuous improvement.
Contribute to engineering excellence through design reviews, code reviews, pair programming, and mentorship, helping raise the bar for software quality and AI-ready architecture across the organization.
Requirements
Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
Significant experience building and shipping production software in a product-focused environment, with a track record of owning complex initiatives end-to-end.
Deep expertise in TypeScript / JavaScript and strong experience building modern web applications using technologies such as Web Components, React, ES6, TypeScript, Redux, or MobX.
Strong experience designing and owning backend services using Node.js, Java, or similar technologies.
Hands-on experience working directly with AI systems, including LLM APIs, generative AI capabilities, prompt engineering, context engineering, or AI-powered product workflows.
Proven ability to architect and implement scalable, efficient systems in collaboration with large, cross-functional teams.
Strong understanding of software architecture, design patterns, distributed systems, and production engineering tradeoffs.
Experience in troubleshooting complex systems and using strong judgment to evaluate multiple technical solutions.
Ability to thrive in fast-moving, ambiguous environments with high ownership and bias for action.
Familiarity with modern engineering tools and workflows such as GitHub, VS Code or Cursor, Bazel, and AI-assisted coding tools.