Generative AI Engineer

As a Generative AI Engineer at our company, you will be an integral part of our AI team, where you will design, develop, and deploy cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models for enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Key Responsibilities: - Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. - Build and fine-tune LLM-based applications such as chatbots, document Q&A systems, report generators, code assistants, and summarization tools. - Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. - Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. - Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. - Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. - Monitor model performance, detect drift, and drive continuous improvement. - Optimize inference performance and cost through model compression, quantization, and API optimization. - Ensure compliance with AI ethics, security, and governance standards. - Prepare and curate training datasets (structured/unstructured text, images, code). - Apply data preprocessing, tokenization, and embedding generation techniques. - Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. - Partner with business stakeholders to identify and shape impactful AI use cases. - Contribute to the development of a strategic AI adoption roadmap and reusable AI Workbench/platform components. Qualifications Required: - Overall 7+ years of experience and relevant 4+ years of GenAI. - Strong programming skills in Python (preferred), with experience in Java or Node.js. - Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. - Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. - Familiarity with RAG pipelines, embedding models, and vector databases. - Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. - Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Vertex AI, Azure ML). - Strong understanding of data engineering, data pipelines, and ETL workflows. - Excellent problem-solving, communication, and stakeholder engagement skills. - Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. As a Generative AI Engineer at our company, you will be an integral part of our AI team, where you will design, develop, and deploy cutting-edge Generative AI solutions using LLMs, Transformers, and Diffusion models for enterprise-grade applications such as intelligent chatbots, document summarization, code assistants, and more. Key Responsibilities: - Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. - Build and fine-tune LLM-based applications such as chatbots, document Q&A systems, report generators, code assistants, and summarization tools. - Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. - Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js. - Collaborate with architects to define scalable, secure, and cost-efficient AI service architectures. - Implement AI/ML pipelines for training, validation, and deployment using tools like MLflow, Vertex AI, or Azure ML. - Monitor model performance, detect drift, and drive continuous improvement. - Optimize inference performance and cost through model compression, quantization, and API optimization. - Ensure compliance with AI ethics, security, and governance standards. - Prepare and curate training datasets (structured/unstructured text, images, code). - Apply data preprocessing, tokenization, and embedding generation techniques. - Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Chroma) for semantic search and retrieval. - Partner with business stakeholders to identify and shape impactful AI use cases. - Contribute to the development of a strategic AI adoption roadmap and reusable AI Workbench/platform components. Qualifications Required: - Overall 7+ years of experience and relevant 4+ years of GenAI. - Strong programming skills in Python (preferred), with experience in Java or Node.js. - Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. - Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. - Familiarity with RAG pipelines, embedding models, and vector databases. - Experience with cloud platforms (A