Job Title

Role Overview:We’re looking for an AI Engineer for one of our Tier-1 IT clients with hands-on experience in building, fine-tuning, and optimizing LLM-based applications. The ideal candidate will have solid expertise in RAG (Retrieval-Augmented Generation) architectures, parameter-efficient fine-tuning (e.g., LoRA), and model quantization techniques for deployment efficiency. Key Responsibilities: ●     Design, implement, and optimize end-to-end LLM-based solutions for real-world applications.●     Develop and maintain RAG pipelines integrating vector databases, embeddings, and retrieval techniques.●     Fine-tune pre-trained language models using LoRA or similar methods.●     Apply quantization and optimization strategies to deploy models efficiently on constrained environments.●     Collaborate with data scientists, software engineers, and product teams to integrate AI features into production systems.●     Monitor, evaluate, and continuously improve model performance and reliability. Required Skills:●     3–5 years of experience in AI/ML development or applied NLP.●     Proficient in Python and frameworks such as PyTorch or TensorFlow.●     Strong understanding of LLM architectures (e.g., GPT, Llama, Falcon, Mistral).●     Experience with RAG frameworks (LangChain, LlamaIndex, or custom retrieval setups).●     Hands-on knowledge of LoRA, PEFT, and model quantization (GPTQ, AWQ, or similar).●     Familiarity with vector databases like FAISS, Pinecone, or ChromaDB.●     Good understanding of prompt engineering and evaluation techniques.●     Cloud deployment experience (AWS, Azure, or GCP) is an advantage. Preferred Skills:●     Exposure to open‑source models and fine-tuning pipelines.●     Experience integrating AI models into web or enterprise products.●     Knowledge of containerization and MLOps (Docker, Kubernetes, MLflow).