Domain Knowledge:
Robust understanding of machine learning and deep learning concepts
Experience with LLMs, prompt engineering, and AI APIs
Knowledge of RAG, embeddings, vector databases (preferred)
Programming: Python (mandatory), JavaScript (preferred)
Frontend: React / Angular / Vue
Backend: Node.js / Python frameworks (FastAPI, Flask, Django)
Experience with Google Cloud Platform (GCP)
Knowledge of Docker Kubernetes (K8s)
Hands-on experience with Model Context Protocol (MCP)
Solid working knowledge of Linux systems and Windows CMD / PowerShell
Design and build end-to-end AI/ML projects from scratch
Develop Agentic AI systems (multi-step workflows, AI agents, automation pipelines)
Implement Model Context Protocol (MCP) for tool integration and context handling
Build and maintain full-stack applications for AI solutions
Integrate LLMs, APIs, and ML models into production-ready systems
Work on data preprocessing, model deployment, and optimization
Deploy solutions on cloud (GCP) and containerized environments (Docker/K8s)
Handle system-level operations using Linux and Windows scripting
Continuously improve system performance and scalability
Bachelor s degree in CSE / IT / Mechanical / or related field
Proven experience in building and delivering AI-based applications
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