We are looking for an experienced Full Stack AI Developer with strong hands-on expertise in TypeScript, React, Node.js/Express, REST APIs, and modern AI application development.

The role will involve designing scalable full-stack architectures, building enterprise-grade applications, and integrating LLMs, RAG, agentic workflows, and AI evaluation capabilities into production systems.

The ideal candidate should have strong software engineering fundamentals and the ability to work across frontend, backend, distributed systems, and AI application layers.

Key Responsibilities:

- Design, develop, and evolve scalable full-stack applications using TypeScript, React, Node.js, and Express.

- Design robust TypeScript architectures with strong type safety, modularity, reusability, and maintainability across frontend and backend systems.

- Develop advanced React applications and component architectures for large-scale enterprise products.

- Design, develop, and maintain scalable Node.js/Express backend services and RESTful APIs.

- Build reliable, high-performance services with appropriate focus on scalability, security, observability, and maintainability.

- Develop and integrate LLM-powered applications using prompt engineering, RAG, tool calling, and agentic workflows.

- Build AI-enabled features using retrieval pipelines, embeddings, vector search, and context-management techniques.

- Implement and optimize agentic workflows, orchestration, and AI application pipelines.

- Develop asynchronous and distributed processing solutions using Redis, BullMQ, or equivalent technologies.

- Implement AI evaluation and quality frameworks to assess relevance, accuracy, reliability, latency, and other model/application metrics.

- Optimize SQL queries, data access patterns, and backend performance for high-volume applications.

- Design and implement containerized, cloud-native applications using Docker and modern deployment practices.

- Apply distributed-systems principles to build resilient, scalable, and fault-tolerant services.

- Collaborate with Product, UX, Data, AI, DevOps, and Architecture teams to deliver end-to-end solutions.

- Participate in technical design discussions, code reviews, architecture reviews, testing, and production support.

- Troubleshoot complex frontend, backend, API, distributed-system, and AI application issues and drive root-cause resolution.

- Establish reusable engineering patterns, coding standards, testing practices, and development best practices.

- Stay current with modern AI platform engineering, LLM application development, and full-stack architecture trends.

Required Skills & Experience:

- 5 - 10 years of experience in full-stack software development with strong production engineering experience.

- Strong hands-on expertise in TypeScript, React, Node.js, and Express.

- Strong understanding of TypeScript architecture, type safety, generics, interfaces, and scalable code organization.

- Strong experience building modern React applications, reusable components, hooks, state management, and frontend architecture.

- Strong experience developing RESTful APIs and backend services using Node.js/Express.

- Strong understanding of API design, authentication/authorization, error handling, validation, and service integration.

- Hands-on experience with LLM application development, prompt engineering, RAG, and agentic workflows.

- Strong understanding of LLMs, embeddings, vector search, context management, and AI application architecture.

- Experience with AI evaluation and techniques for measuring and improving AI application quality.

- Hands-on experience with Redis and/or BullMQ for caching, queues, asynchronous processing, or background jobs.

- Strong SQL skills with experience in query optimization, data modelling, and efficient data access.

- Good understanding of distributed systems, microservices, asynchronous processing, and fault-tolerant architectures.

- Experience with Docker and cloud-native application development.

- Strong understanding of Git, CI/CD, testing, debugging, and production support practices.

- Strong analytical and problem-solving skills with the ability to work across both software and AI engineering challenges.

- Good communication and cross-functional collaboration skills.