Job Description
Job Tittle : Senior AI Engineer (RAG & LLM Systems)
Experience : 8-10 years (only)
We are seeking a Senior AI Engineer with 8–10 years of experience to architect and deploy production-grade GenAI solutions. As a technical leader, you will design scalable Retrieval-Augmented Generation (RAG) pipelines, integrating advanced vector search with state-of-the-art LLMs to deliver high-accuracy enterprise applications.
What You’ll Do:
Architect end-to-end AI systems using LangChain, LlamaIndex , or custom orchestration frameworks.
Optimize retrieval performance using vector databases like Pinecone, Weaviate, or Milvus .
Deploy and fine-tune models from OpenAI, Anthropic, and Meta (Llama) within cloud environments (AWS/GCP/Azure).
Lead MLOps initiatives to ensure seamless model monitoring and scalability.
What You Bring:
Deep expertise in Python, PyTorch/TensorFlow , and NLP.
Proven track record of moving GenAI projects from R&D to production.
Mastery of embeddings, similarity search, and prompt engineering.
Strong system design skills and experience with MLOps tools like MLflow or Kubeflow .
Experience : 8-10 years (only)
We are seeking a Senior AI Engineer with 8–10 years of experience to architect and deploy production-grade GenAI solutions. As a technical leader, you will design scalable Retrieval-Augmented Generation (RAG) pipelines, integrating advanced vector search with state-of-the-art LLMs to deliver high-accuracy enterprise applications.
What You’ll Do:
Architect end-to-end AI systems using LangChain, LlamaIndex , or custom orchestration frameworks.
Optimize retrieval performance using vector databases like Pinecone, Weaviate, or Milvus .
Deploy and fine-tune models from OpenAI, Anthropic, and Meta (Llama) within cloud environments (AWS/GCP/Azure).
Lead MLOps initiatives to ensure seamless model monitoring and scalability.
What You Bring:
Deep expertise in Python, PyTorch/TensorFlow , and NLP.
Proven track record of moving GenAI projects from R&D to production.
Mastery of embeddings, similarity search, and prompt engineering.
Strong system design skills and experience with MLOps tools like MLflow or Kubeflow .
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