Generative AI Engineer

Experience: 5-10 years
Job Summary:
We are looking for an experienced Generative AI Engineer to join our AI/ML team. In this role, you will design, develop, and deploy solutions powered by generative models like LLMs (e.g., GPT, LLaMA), diffusion models, and multimodal AI. You will work closely with product managers, data scientists, and engineering teams to create cutting-edge applications across domains like content generation, code assistants, chatbots, synthetic data, or digital twins. Key Responsibilities: Design and develop scalable GenAI-powered solutions using LLMs, transformers, or diffusion models. Fine-tune, evaluate, and optimize pre-trained models for domain-specific use cases. Build secure and efficient pipelines for prompt engineering, retrieval-augmented generation (RAG), and embeddings. Work with APIs (e.g., OpenAI, Anthropic, Cohere, Hugging Face) or open-source models (e.g., Mistral, LLaMA, Falcon). Collaborate with cross-functional teams to integrate GenAI into existing products and workflows. Stay up to date with emerging research in GenAI, multi-modal models, and AI safety. Ensure responsible AI practices, including data privacy, bias mitigation, and model explainability. Required Skills & Experience: 5+ years in AI/ML, with at least 1–2 years in generative AI or LLM applications. Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow). Hands-on experience with prompt engineering, model fine-tuning, vector databases (e.g., FAISS, Pinecone), and RAG pipelines. Knowledge of Hugging Face Transformers, LangChain, LlamaIndex or similar toolkits. Solid understanding of transformer architectures, tokenization, attention mechanisms. Experience with MLOps tools and deploying models to production (Docker, FastAPI, Kubernetes, etc.) Good to Have: Experience with diffusion models (e.g., for image/video generation). Exposure to GenAI use cases in domains like healthcare, finance, or education. Contributions to open-source GenAI projects or AI research publications.