Overview

Location: Noida (Hybrid-3 days)

Experience: 10–13 Years

Key Responsibilities

• Build and deploy end-to-end Generative AI applications.
• Design and implement LLM-based architectures, RAG pipelines, and AI agents.
• Develop scalable, secure, and cost-efficient AI solutions.
• Optimize prompts, embeddings, and LLM performance.
• Collaborate with product, engineering, and business teams.
• Implement testing, monitoring, and MLOps practices for GenAI.
• Build POCs, conduct experiments, and stay updated with the latest AI trends.

Required Skills

• Generative AI application development (end-to-end)
• Large Language Models (LLMs)
• RAG (Retrieval-Augmented Generation)
• LangChain
• OpenAI SDK
• AWS Bedrock & Bedrock Agents
• CrewAI / AutoGen
• Prompt Engineering
• AI Agents
• Vector Databases (Pinecone, Weaviate, Qdrant, Milvus, ChromaDB)
• Python
• Hugging Face, PyTorch/TensorFlow, Scikit-learn, Pandas, NumPy
• LoRA / QLoRA
• NLP fundamentals
• MLOps for LLMs
• CI/CD for AI applications
• AWS Cloud

Required Experience

• 3–7 years of experience in Data Science/AI/ML.
• Minimum 2+ years of hands-on experience with Generative AI applications.
• Strong expertise in Python and modern AI/ML frameworks.
• Experience with AWS (preferred) and cloud-based AI deployments.
• Hands-on experience with AI coding assistants like GitHub Copilot, Cursor, or Amazon Q is a plus.

Preferred Skills

• Experience with React, Streamlit, or Gradio.
• Azure OpenAI or Google Vertex AI.
• Contributions to open-source GenAI projects.
• Experience with advanced LLM MLOps practices.