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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Assess the commercial potential and technical readiness levels of internal R&D projects for potential spin-offs or new business incubation.
Bachelor's degree in Engineering (e.g., Electrical, Mechanical, Chemical, Software, Materials Science, Biomedical) or a relevant scientific discipline from an accredited institution.
Master's or Ph.D. in a relevant engineering or scientific field is highly preferred.
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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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You will work across the entire stack — from frontend experiences and APIs to distributed systems, data infrastructure, LLM orchestration, agentic workflows, evaluation systems, and autonomous optimization loops.
The ideal candidate has deep hands-on experience with Claude/Anthropic models, agentic architectures, tool-use, multi-step reasoning, autonomous execution loops, and AI-driven self-optimization.
You should be comfortable asking: "How can we make the system improve itself rather than requiring an engineer to manually optimize every workflow?"
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You will work across the entire stack — from frontend experiences and APIs to distributed systems, data infrastructure, LLM orchestration, agentic workflows, evaluation systems, and autonomous optimization loops.
The ideal candidate has deep hands-on experience with Claude/Anthropic models, agentic architectures, tool-use, multi-step reasoning, autonomous execution loops, and AI-driven self-optimization.
You should be comfortable asking: "How can we make the system improve itself rather than requiring an engineer to manually optimize every workflow?"
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