Fullstack AI Engineer

We are looking for a highly skilled Fullstack AI Engineer to build and deploy intelligent, user-facing applications powered by modern AI technologies. This role sits at the intersection of AI/ML, backend systems, and frontend development, enabling the creation of scalable, production-ready AI solutions.

You will work closely with product managers, designers, and data teams to develop AI-driven features such as copilots, chat interfaces, recommendation systems, and document intelligence platforms., * Design and develop end-to-end AI-powered applications (frontend + backend)

• Build and integrate LLM-based features (chatbots, copilots, summarization, Q&A systems)
• Develop scalable backend services and APIs to serve AI models
• Create intuitive and responsive frontend interfaces using modern frameworks
• Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases
• Work with data pipelines for ingestion, preprocessing, and embedding generation
• Optimize application performance, latency, and scalability
• Collaborate with data scientists to deploy models into production
• Implement prompt engineering and evaluation strategies
• Ensure security, privacy, and responsible AI practices
• Integrate AI workflows into CI/CD pipelines
• Troubleshoot and debug across the full stack

• 4-8 years of experience in full stack software development
• Strong proficiency in JavaScript/TypeScript and modern frontend frameworks (React.js, Next.js)
• Backend experience with Python, Node.js, or Java
• Hands-on experience with AI/ML or Generative AI applications
• Experience working with LLMs (OpenAI, Hugging Face, or similar APIs)
• Strong understanding of REST APIs and microservices architecture
• Experience with databases (SQL and NoSQL)
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform)
• Experience with Git, CI/CD pipelines, and Agile development, * Experience with LangChain, LlamaIndex, or similar frameworks
• Knowledge of vector databases (Pinecone, FAISS, Weaviate)
• Experience implementing RAG architectures
• Familiarity with Docker and Kubernetes
• Exposure to streaming/data pipelines (Kafka, Spark)
• Experience in financial services or fintech
• Understanding of AI evaluation, prompt tuning, and model optimization, * Full Stack Development (Frontend + Backend)
• Generative AI / LLM Integration
• API Development & Microservices
• Cloud & Deployment
• Prompt Engineering & AI Workflows
• Problem Solving & Product Thinking