Job Overview We are seeking a highly experienced and innovative Senior AI Engineer with a strong background in Generative AI , including LLM fine-tuning and prompt engineering . This role requires hands-on expertise across NLP , Computer Vision , and AI agent-based systems , with the ability to build, deploy, and optimize scalable AI solutions using modern tools and frameworks. Required Skills & Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related field. 5+ years of hands-on experience in AI/ML solution development. Proven expertise in fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, GPT-family) using techniques like LoRA, QLoRA, PEFT. Deep experience in prompt engineering, including zero-shot, few-shot, and retrieval-augmented generation (RAG). Proficient in key AI libraries and frameworks: LLMs & GenAI: Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Diffusers NLP: SpaCy, NLTK. Vision: OpenCV, MMDetection, YOLOv5/v8, Detectron2 MLOps: MLflow, FastAPI, Docker, Git Familiarity with vector databases (Pinecone, FAISS, Weaviate) and embedding generation. Experience with cloud platforms like AWS, GCP, or Azure, and deployment on in house GPU-backed infrastructure. Strong communication skills and ability to convert business problems into technical solutions. Preferred Qualifications Experience building multimodal systems (text + image, etc.) Practical experience with agent frameworks for autonomous or goal-directed AI. Familiarity with quantization, distillation, or knowledge transfer for efficient model deployment. Key Responsibilities Design, fine-tune, and deploy generative AI models (LLMs, diffusion models, etc.) for real-world applications. Develop and maintain prompt engineering workflows, including prompt chaining, optimization, and evaluation for consistent output quality. Build NLP solutions for Q&A, summarization, information extraction, text classification, and more. Develop and integrate Computer Vision models for image processing, object detection, OCR, and multimodal tasks. Architect and implement AI agents using frameworks such as LangChain, AutoGen, CrewAI, or custom pipelines. Collaborate with cross-functional teams to gather requirements and deliver tailored AI-driven features. Optimize models for performance, cost-efficiency, and low latency in production. Continuously evaluate new AI research, tools, and frameworks and apply them where relevant. Mentor junior AI engineers and contribute to internal AI best practices and documentation. Skills:- Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Large Language Models (LLM), Prompt engineering, Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), Computer Vision, AI Agents, Vector database, Python, Docker and API