Generative AI Engineer

Hiring Generative AI Engineer Role Overview We are looking for a Generative AI Engineer with 3-4 years of experience in Machine Learning and AI application development. The ideal candidate should have strong ML fundamentals and handson experience in designing and building GenAI solutions using Large Language Models (LLMs), RAG, and AI Agent frameworks. Key Responsibilities Design, develop, and deploy Generative AI applications. Build RAG pipelines using embeddings and vector databases. Develop AI Agents and integrate LLMs with enterprise applications. Optimize prompts, retrieval, and model performance. Collaborate with cross-functional teams to deliver scalable AI solutions. Stay updated with the latest advancements in GenAI technologies. Required Skills Strong Python programming skills. Good understanding of Machine Learning and Deep Learning fundamentals. Handson experience with LLMs, Prompt Engineering, RAG, and AI Agents. Experience with LangChain, LangGraph, or similar GenAI frameworks. Knowledge of vector databases such as PGVector, Milvus, Pinecone, Chroma, or FAISS. Experience with SQL/PostgreSQL and REST APIs. Familiarity with Hugging Face, Transformer models, and embedding models. Basic understanding of Docker, Git, and cloud platforms (AWS/Azure/GCP). Preferred Skills Finetuning using LoRA/QLoRA. Experience with opensource LLMs (Llama, Gemma, Qwen, Mistral). Knowledge of LLM evaluation, guardrails, and AI safety. Exposure to Knowledge Graphs or GraphRAG is a plus. Hiring Generative AI Engineer Role Overview We are looking for a Generative AI Engineer with 3-4 years of experience in Machine Learning and AI application development. The ideal candidate should have strong ML fundamentals and handson experience in designing and building GenAI solutions using Large Language Models (LLMs), RAG, and AI Agent frameworks. Key Responsibilities Design, develop, and deploy Generative AI applications. Build RAG pipelines using embeddings and vector databases. Develop AI Agents and integrate LLMs with enterprise applications. Optimize prompts, retrieval, and model performance. Collaborate with cross-functional teams to deliver scalable AI solutions. Stay updated with the latest advancements in GenAI technologies. Required Skills Strong Python programming skills. Good understanding of Machine Learning and Deep Learning fundamentals. Handson experience with LLMs, Prompt Engineering, RAG, and AI Agents. Experience with LangChain, LangGraph, or similar GenAI frameworks. Knowledge of vector databases such as PGVector, Milvus, Pinecone, Chroma, or FAISS. Experience with SQL/PostgreSQL and REST APIs. Familiarity with Hugging Face, Transformer models, and embedding models. Basic understanding of Docker, Git, and cloud platforms (AWS/Azure/GCP). Preferred Skills Finetuning using LoRA/QLoRA. Experience with opensource LLMs (Llama, Gemma, Qwen, Mistral). Knowledge of LLM evaluation, guardrails, and AI safety. Exposure to Knowledge Graphs or GraphRAG is a plus.