Generative AI Engineer (3-8 Years Experience)

About the job

Description

About the Role

Our client is looking for a skilled Senior Generative AI Engineer with 38 years of hands-on experience in building, fine-tuning, and deploying generative models. The ideal candidate will have strong expertise in large language models (LLMs), prompt engineering, and scalable AI systems, along with a solid understanding of modern GenAI frameworks and tools.

Key Responsibilities

• Design, develop, and deploy generative AI solutions using LLMs and foundation models
• Build and optimize applications leveraging text, image, or multimodal generation
• Develop and refine prompts, chains, and agents for high-quality outputs
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Fine-tune pre-trained models for domain-specific use cases
• Integrate AI models into production using APIs, microservices, or cloud platforms
• Collaborate with cross-functional teams to deliver AI-driven products
• Monitor model outputs, improve performance, and ensure responsible AI usage
• Stay updated with the latest advancements in Generative AI and LLM ecosystems

Required Skills & Qualifications

• Bachelors or Masters degree in Computer Science, AI, Data Science, or related field
• 38 years of experience in AI/ML with exposure to Generative AI projects
• Strong programming skills in Python (mandatory)
• Hands-on experience with LLMs such as GPT, LLaMA, Claude, or similar models
• Experience with frameworks/tools like LangChain, LlamaIndex, Hugging FaceSolid understanding of:
• Generative AI concepts
• Prompt Engineering techniques
• Transformers architecture
• Experience working with vector databases (FAISS, Pinecone, Weaviate, etc.)
• Familiarity with APIs, embeddings, and semantic search
• Experience in deploying models using REST APIs, Docker, or cloud services

Preferred Qualifications

• Experience with cloud platforms like AWS (Bedrock, SageMaker), Azure OpenAI, Google Vertex AI
• Knowledge of LLMOps / MLOps tools
• Experience with multimodal AI (text, image, audio)
• Familiarity with fine-tuning techniques (LoRA, PEFT, etc.)