Full-Stack AI Engineer (React, Node, AI)

Job Description

We are seeking a Full-Stack AI Engineer with strong hands-on experience in React, Node.js, and AI/ML technologies. The ideal candidate will design, build, and scale AI-powered web applications, working across frontend, backend, and AI integration layers.

Key Responsibilities

• Design and develop end-to-end full-stack applications using React and Node.js
• Build and integrate AI/ML solutions (LLMs, NLP, recommendation systems, chatbots, etc.) into products
• Develop scalable REST / GraphQL APIs and backend services
• Integrate AI models using platforms like OpenAI, Hugging Face, LangChain, or custom models
• Optimize application performance, scalability, and security
• Collaborate with product, data, and design teams to deliver AI-driven features
• Handle deployments, monitoring, and production support
  
  

• Minimum 5+years of experience in Java (Java 8 or above).
• Hands-on experience with Spring Boot, Spring MVC, Spring Data JPA, and Spring Security
• Experience in building microservices-based architectures.
• Strong knowledge of RESTful web services and API design.
• Experience with databases: Oracle, MySQL, PostgreSQL, or similar.
• Familiarity with Hibernate/JPA.
• Knowledge of banking and financial domain concepts (e.g., payments, loans, accounts, treasury, risk, compliance, etc.).
• Experience with CI/CD pipelines, Git, Maven/Gradle, Jenkins.
• Understanding of security protocols (OAuth2, JWT, encryption, etc.).
• Strong problem-solving and debugging skills
  
  

• Strong experience with React.js (hooks, state management, performance optimization)
• Solid backend expertise in Node.js (Express/NestJS)
• Hands-on experience with AI/ML integration (LLMs, embeddings, vector databases)
• Experience with Python for AI workflows is a plus
• Knowledge of databases (PostgreSQL, MongoDB, Redis)
• Experience with cloud platforms (AWS / Azure / GCP)
• Familiarity with Docker, CI/CD, and microservices architecture
  
  

• Experience with LLMs, prompt engineering, RAG pipelines
• Understanding of model inference, fine-tuning, and AI APIs
• Knowledge of vector databases (Pinecone, FAISS, Weaviate, etc.)
• Awareness of AI security, ethics, and performance optimization
  
  

• Experience building AI-powered SaaS products
• Exposure to MLOps concepts
• Startup or product-driven development experience
  
  

• Strong hands-on coder (not just design/architecture)
• Problem-solver with a product mindset
• Comfortable working end-to-end across the stack