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

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 Required Skills & Qualifications 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.
Technical Skills Required 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 AI & Data Skills 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 Nice to Have Experience building AI-powered SaaS products Exposure to MLOps concepts Startup or product-driven development experience What We’re Looking For Strong hands-on coder (not just design/architecture) Problem-solver with a product mindset Comfortable working end-to-end across the stack