AI Engineer (RAG / LLM / GenAI)
Indexed description
You will work closely with Data Engineers, ML Engineers, and Product teams to design and deploy cutting-edge AI systems in production environments.
Key Responsibilities
- Design and implement RAG-based architectures integrating LLMs with enterprise data sources
- Develop, fine-tune, and optimize Large Language Models (LLMs) for domain-specific use cases
- Build end-to-end GenAI applications (chatbots, copilots, summarization, Q&A systems)
- Develop scalable pipelines for data ingestion, embedding, vector search, and retrieval
- Apply Deep Machine Learning techniques for model training, evaluation, and optimization
- Integrate AI solutions with APIs, microservices, and cloud platforms
- Ensure model performance, scalability, and security compliance
- Collaborate with cross-functional teams to translate business problems into AI solutions
- Strong hands-on experience with:
- RAG (Retrieval-Augmented Generation) frameworks
- LLMs (e.g., GPT, LLaMA, Claude, etc.)
- Generative AI application development
- Deep understanding of Machine Learning & Deep Learning concepts
- Experience with:
- Python, PyTorch, TensorFlow
- Vector databases (Pinecone, FAISS, Weaviate, Chroma)
- Embedding models and semantic search
- Experience with prompt engineering and LLM fine-tuning
- Strong knowledge of APIs, microservices, and system design
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