GEN AI

Job description

**Job Title: Generative AI Engineer / AI Engineer** **Experience:** 2 11 Years **Employment Type:** Full-Time **Job Summary** We are seeking a passionate **Generative AI Engineer** to design, develop, and deploy AI-powered solutions using state-of-the-art large language models (LLMs), multimodal models, and machine learning frameworks. The ideal candidate will have hands-on experience in building GenAI applications, prompt engineering, fine-tuning models, and integrating AI solutions into production systems. **Key Responsibilities** - Design and develop **Generative AI applications** using LLMs (GPT, Llama, Claude, etc.) - Build **end-to-end AI pipelines** including data ingestion, preprocessing, model training, and deployment - Implement **prompt engineering and prompt optimization techniques** - Develop and maintain **RAG (Retrieval-Augmented Generation)** systems - Fine-tune and customize open-source and proprietary large language models - Integrate AI services via APIs and SDKs into enterprise applications - Work with vector databases (FAISS, Pinecone, Weaviate, ChromaDB) - Ensure model performance, scalability, and reliability in production - Collaborate with cross-functional teams (Data Scientists, DevOps, Backend Engineers) - Monitor and evaluate LLM outputs for accuracy, safety, and bias - Stay updated with latest advancements in AI/ML and GenAI ecosystems **Required Skills** - Strong programming skills in **Python** - Experience with **Generative AI frameworks**: - LangChain, LlamaIndex, Semantic Kernel - Hands-on experience with **LLMs**: - OpenAI GPT, Hugging Face, Llama, Mistral, etc. - Knowledge of **prompt engineering techniques** - Experience with **vector databases** - Familiarity with **RAG architectures** - Understanding of **ML/DL fundamentals** - Experience with REST APIs and microservices **Preferred Skills** - Experience in **fine-tuning LLMs** (LoRA, PEFT, RLHF) - Knowledge of **multi-modal models (text, image, audio)** - Exposure to **MLOps tools** (MLflow, Kubeflow, Airflow) - Experience with **cloud platforms** (AWS, Azure, GCP) - Familiarity with **Docker, Kubernetes** - Understanding of **data pipelines and big data tools** - Knowledge of **LLM evaluation frameworks** **Tools & Technologies** - Languages: Python, SQL - Frameworks: PyTorch, TensorFlow - GenAI Tools: LangChain, LlamaIndex - Databases: Pinecone, FAISS, ChromaDB - Cloud: AWS / Azure / GCP - DevOps: Docker, Kubernetes