(15h Left) Generative AI Engineer

1 week ago

Bengaluru, India PROADSW3 Relations pvt. ltd. Full time

🚀 Job Title: Generative AI Engineer (LLM | Python | AWS | FastAPI) 📍 Location: Bangalore, India 5+ years of experience 💼 Employment Type: Permanent 💰 Budget: Up to ₹30 LPA 🕐 Notice Period: Immediate Joiners Preferred About the Role We are seeking a highly skilled Generative AI Engineer with a strong foundation in Python, Large Language Models (LLMs), AWS, and FastAPI. In this role, you will design, develop, and deploy scalable AI-driven systems and GenAI solutions that push the boundaries of automation, intelligent APIs, and AI-assisted decision-making. This position offers a unique opportunity to work on cutting-edge GenAI applications, integrate LLMs into production systems, and collaborate with cross-functional teams to create next-generation AI capabilities. Key Responsibilities - Design, fine-tune, and deploy Large Language Models (LLMs) for real-world use cases such as chatbots, text summarization, and knowledge retrieval. - Develop end-to-end AI pipelines using Python and FastAPI, ensuring performance, scalability, and maintainability. - Build and deploy API-driven GenAI services and integrate them into cloud-native environments (AWS preferred). - Leverage AWS services (Lambda, S3, EC2, SageMaker, API Gateway) for scalable AI model hosting and automation. - Collaborate with data scientists and MLOps engineers to improve model training, evaluation, and deployment pipelines. - Implement prompt engineering, retrieval-augmented generation (RAG), and custom embeddings for enterprise-level AI applications. - Ensure data security, version control, and model governance throughout the AI lifecycle. - Conduct continuous performance optimization of AI systems and stay updated on the latest in Generative AI and LLM research. Must-Have Skills - Programming: Expert in Python (OOPs, Async, API integration). - Frameworks: FastAPI (must-have), Flask (good to have). - AI/ML: Hands-on experience with LLMs, Prompt Engineering, LangChain, or RAG pipelines. - Cloud: Proficiency in AWS (Lambda, SageMaker, EC2, S3, API Gateway). - MLOps: Experience with model deployment, Docker, CI/CD, and API-based inference. - Strong knowledge of NLP concepts, embeddings, and fine-tuning pre-trained transformer models (e.g., GPT, LLaMA, Falcon, Mistral). Good to Have - Experience with Vector Databases (FAISS, Pinecone, Weaviate, or Chroma). - Familiarity with OpenAI APIs, Hugging Face Transformers, and LangChain Framework. - Exposure to frontend AI integrations (Streamlit, Gradio, etc.) for demo or prototyping. - Understanding of Data Engineering workflows and API orchestration.

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