Senior Python Engineer

Role Overview You are a Senior Python Engineer | LLM & Generative AI Architect responsible for leading the design, development, and deployment of production-grade Generative AI solutions. Your role will involve transforming business problems into high-performance, cost-optimized AI systems running in real-world environments. Specifically, you will work on building scalable and reliable LLM systems such as RAG pipelines, fine-tuned models, and AI-powered APIs. Key Responsibilities - Design, implement, and optimize LLM-based and Generative AI solutions for production use - Architect and lead Retrieval-Augmented Generation (RAG) systems for context-aware applications - Perform LLM fine-tuning, calibration, and prompt optimization to improve accuracy, latency, and cost efficiency - Build and manage end-to-end ML pipelines, including data ingestion, embeddings generation, and vector indexing - Work with vector databases to enable fast and reliable semantic search - Integrate deployed AI models into existing platforms through scalable and secure APIs - Collaborate with engineering and product teams to ensure smooth production rollout and maintenance Required Technical Skills & Experience - 6+ years of production-level Python development - Strong hands-on experience with Large Language Models (LLMs) and Generative AI systems - Proficiency in PyTorch or TensorFlow for model training and inference - Practical experience with Hugging Face Transformers ecosystem - Hands-on expertise with LangChain or LlamaIndex for LLM orchestration - Experience working with Vector Databases such as Pinecone, Weaviate, or Milvus - Solid understanding of embeddings, semantic search, and RAG pipelines - Working knowledge of MLOps, including model deployment, monitoring, and lifecycle management in cloud environments Role Overview You are a Senior Python Engineer | LLM & Generative AI Architect responsible for leading the design, development, and deployment of production-grade Generative AI solutions. Your role will involve transforming business problems into high-performance, cost-optimized AI systems running in real-world environments. Specifically, you will work on building scalable and reliable LLM systems such as RAG pipelines, fine-tuned models, and AI-powered APIs. Key Responsibilities - Design, implement, and optimize LLM-based and Generative AI solutions for production use - Architect and lead Retrieval-Augmented Generation (RAG) systems for context-aware applications - Perform LLM fine-tuning, calibration, and prompt optimization to improve accuracy, latency, and cost efficiency - Build and manage end-to-end ML pipelines, including data ingestion, embeddings generation, and vector indexing - Work with vector databases to enable fast and reliable semantic search - Integrate deployed AI models into existing platforms through scalable and secure APIs - Collaborate with engineering and product teams to ensure smooth production rollout and maintenance Required Technical Skills & Experience - 6+ years of production-level Python development - Strong hands-on experience with Large Language Models (LLMs) and Generative AI systems - Proficiency in PyTorch or TensorFlow for model training and inference - Practical experience with Hugging Face Transformers ecosystem - Hands-on expertise with LangChain or LlamaIndex for LLM orchestration - Experience working with Vector Databases such as Pinecone, Weaviate, or Milvus - Solid understanding of embeddings, semantic search, and RAG pipelines - Working knowledge of MLOps, including model deployment, monitoring, and lifecycle management in cloud environments