01Key Responsibilities
Design and develop end-to-end AI applications (frontend, backend, and AI/ML layers) Build, train, and deploy machine learning / GenAI models (e.g., LLMs, RAG pipelines) Develop APIs and microservices for model serving and integration Build responsive user interfaces for AI-driven applications Integrate AI solutions with enterprise systems and data platforms Ensure scalability, performance, and reliability of AI applications Implement MLOps practices (CI/CD, monitoring, model versioning) Collaborate with data engineers, product teams, and business stakeholders Required Skills & Qualifications: Bachelors/Masters degree in Computer Science, AI, or related field Strong programming skills in Python and one frontend/backend framework (e.g., React, Node.js, FastAPI) Experience with machine learning / deep learning frameworks (Scikit-learn, TensorFlow, PyTorch) Hands-on experience building REST APIs and web applications Familiarity with databases (SQL/NoSQL) and data pipelines Experience with cloud platforms (Azure, AWS, or GCP) Strong understanding of software engineering best practices Nice to Have (Highly Valuable): Experience with GenAI/LLMs (OpenAI, Azure OpenAI, LangChain, RAG architectures) Knowledge of vector databases (FAISS, Pinecone, Weaviate) Exposure to Docker, Kubernetes, and DevOps/MLOps pipelines Experience in building AI-powered enterprise applications or agents BE/ B.Tech or equivalent Experience Level Mid Level .
