Help align the design system with company goals by improving efficiency, consistency, and scalability across product teams and brands
Participate in conversations and workshops with stakeholders, users, and contributors to ensure system scalability and strong relationships
Explore and apply AI-assisted development workflows to help the team work more effectively, improve quality, strengthen documentation, and create a better developer experience
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We are seeking an experienced Technical Team Lead with strong Front-End expertise in ReactJS and React Native to lead the technical direction of our web and mobile applications. You will focus primarily on building scalable, responsive and user-friendly front-end solutions, while contributing to Node.js back-end development, API integration, technical improvements and team development.
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Establish and improve front-end frameworks, coding standards and development best practices.
Collaborate with back-end developers on API integration and end-to-end system functionality, with hands-on involvement in Node.js (JavaScript / TypeScript) back-end development where required.
Provide technical support to development teams and clients, including troubleshooting and resolving application issues.
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Collaborate with back-end developers on API integration and end-to-end system functionality, with hands-on involvement in Node.js (JavaScript / TypeScript) back-end development where required.
Provide technical support to development teams and clients, including troubleshooting and resolving application issues.
Review and improve existing solutions to enhance quality, performance and maintainability.
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Full Stack EngineeringFrontend: React, Next.js, TypeScript, modern component architectures, state management, real-time and streaming AI interfaces, agent activity and execution interfaces, data visualization.Backend: Node.js, TypeScript, Python, REST APIs, GraphQL, WebSockets and streaming, event-driven architectures, background workers, job queues, distributed systems, authentication and authorization.
Distributed SystemsDesign systems that reliably execute thousands or millions of AI and data-processing tasks. Kubernetes, Docker, Cloud Run and serverless, message queues, Redis, Kafka or equivalent, distributed job processing, concurrency management, rate limiting, retries, idempotency, fault tolerance, observability. You know how to build systems that stay reliable when agents fail, APIs time out, models hallucinate, or downstream services go away.
Data & Learning InfrastructureBuild the infrastructure agents need to learn from historical executions. PostgreSQL, BigQuery or equivalent data warehouses, ClickHouse or analytical databases, vector databases, embeddings, retrieval systems, event logs, feature stores, analytics pipelines, data ingestion.
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