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Popular fullstack title with broad AI/frontend/backend skills increases applicant density despite smaller company brand.
LLM/RAG and fullstack expertise transfers across industries but needs specialized AI experience.
Many mandatory technical skills and senior-level AI/fullstack expertise make selection strict.
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Design and develop AI-powered applications leveraging Large Language Models (LLMs) and multimodal AI capabilities (text + image).
Build and maintain Retrieval-Augmented Generation (RAG) pipelines integrating vector databases and LLM APIs (OpenAI, Claude, Gemini, etc.).
Develop scalable, responsive full-stack applications with React.js/Next.js frontend and Python/Node.js backend; deploy and optimize on cloud platforms (AWS, Azure, GCP).
Proficiency in Python and JavaScript/TypeScript for full-stack development.
Experience with frontend frameworks React.js and Next.js, and backend frameworks FastAPI or Express.
Hands-on experience with Generative AI concepts including Prompt Engineering, Function Calling, and structured outputs.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in designing and deploying large-scale AI applications integrating multiple LLM APIs and vector databases for RAG workflows.
Comfortable managing end-to-end cloud-based deployments and optimizing AI workloads for performance, scalability, and cost.
Skilled in building robust, scalable full-stack systems with seamless frontend-backend integration and API design (REST/GraphQL).