LLM engineer

Role overview

Responsibilities

• check_circle Develop and maintain natural language search capabilities and semantic search solutions using vector databases.
• check_circle Implement NL-to-SQL pipelines and other intelligent query generation features for analytics platforms.
• check_circle Build and optimize Generative AI features (summarization, recommendations, insights) for analytics applications.
• check_circle Design and implement Agents and Workflows for complex tasks across datasets.
• check_circle Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge retrieval and query resolution.
• check_circle Create embeddings for structured and unstructured data and leverage them for semantic understanding and search.
• check_circle Process and transform structured (tables, CSV, SQL) and unstructured data (text, documents, logs) as input/output for AI models.
• check_circle Collaborate with data engineers, analysts, and product teams to integrate AI features seamlessly into the platform.
• check_circle Evaluate, benchmark, and optimize LLM performance for real-world analytics use cases.
• check_circle Bachelor's or master's degree in computer science, AI/ML, Data Science, or related field.
• check_circle Hands-on experience with LLMs (OpenAI, Anthropic, Cohere, or similar).
• check_circle Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS.
• check_circle Strong understanding of embeddings, semantic search, and their practical applications.
• check_circle Expertise in RAG pipelines, Agents, and Workflow orchestration.
• check_circle Proficiency in Python and relevant AI/ML frameworks (LangChain, HuggingFace, PyTorch, TensorFlow).
• check_circle Familiarity with NL-to-SQL systems and natural language query processing.
• check_circle Experience working with structured and unstructured data sources.
• check_circle Knowledge of data pipelines, preprocessing, and storage formats for analytics.
• check_circle Ability to design scalable, production-ready AI solutions integrated with web applications.

Preferred qualifications

• 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.