LLM engineer

About the Role

Master works is looking for an experienced LLM Engineer to join our team working on next-generation AI-driven analytics solutions. The ideal candidate will design and implement natural language search, semantic search solutions, and generative AI features for our web applications. You will work hands‑on with advanced language models, vector databases, RAG pipelines, and build intelligent workflows to enable actionable insights from both structured and unstructured data.

• Develop and maintain natural language search capabilities and semantic search solutions using vector databases.
• Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.
• Build and optimize generative AI features (summarization, recommendations, insights) for analytics applications.
• Design and implement agents and workflows for complex tasks across datasets.
• Develop RAG (retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.
• Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.
• Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.
• Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.
• Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.

• Bachelor's or master's degree in computer science, AI/ML, data science, or related field.
• Hands‑on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).
• Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
• Strong understanding of embeddings, semantic search, and their practical applications.
• Expertise in RAG pipelines, agents, and workflow orchestration.
• Proficiency in Python and relevant AI/ML frameworks (Lang Chain, Hugging Face, PyTorch, Tensor Flow).
• Familiarity with NL-to-SQL systems and natural language query processing.
• Experience working with structured and unstructured data sources.
• Knowledge of data pipelines, preprocessing, and storage formats for analytics.
• Ability to design scalable, production‑ready AI solutions integrated with web applications.

• Experience working with AI‑based chatbots, natural language search, NL to SQL.
• Knowledge of prompt engineering and fine‑tuning LLMs.
• Familiarity with data privacy, security, and compliance considerations in AI pipelines.

• Strong problem‑solving and analytical skills.
• Excellent communication skills to work with cross‑functional teams.
• Passion for AI and staying up to date with the latest developments in LLMs and generative AI.