Senior Artificial Intelligence Engineer - LLM RAG

We are looking for an experienced AI Engineer specializing in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to develop and optimize AI-driven applications.

The ideal candidate will have hands-on experience in deploying, fine-tuning, and integrating LLMs with RAG architectures to enhance the efficiency and accuracy of AI-powered solutions.

Responsibilities

• Design, develop, and optimize AI solutions using LLMs (e.g., GPT-4, LLaMA, Falcon) and RAG frameworks.
• Implement and fine-tune models to improve response relevance and contextual accuracy.
• Develop pipelines for data retrieval, indexing, and augmentation to improve knowledge grounding.
• Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities.
• Integrate AI models with enterprise applications and APIs.
• Optimize model inference for performance and scalability.
• Collaborate with data scientists, ML engineers, and software developers to align AI models with business objectives.
• Ensure ethical AI implementation, addressing bias, explainability, and data security.
• Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques.
  
  

• 8+ years experience in software development according to development standards;
• Strong experience in training and deploying LLMs using frameworks like Hugging Face Transformers, OpenAI API, or LangChain.
• Proficiency in Retrieval-Augmented Generation (RAG) techniques and vector search methodologies.
• Hands-on experience with vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate.
• Solid understanding of NLP, deep learning, and transformer architectures.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.)
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps workflows.
• Familiarity with containerization (Docker, Kubernetes) for scalable AI deployments.
• Strong problem-solving and debugging skills.
• Excellent communication and teamwork abilities.
• Bachelors or Masters degree in computer science, AI, Machine Learning, or a related field.
  
  

• Help shape a brand-new offering that bridges offline retail with online presence.
• Be a foundational team member alongside Product and QA.
• Gain experience in scaling an operationally heavy, customer-focused tech service.
• Competitive compensation, supportive team, and flexible work model.