Artificial Intelligence Engineer

Job Summary

We are seeking an experienced AI Applications / Solutions Engineer to design, build, and deploy intelligent solutions powered by modern AI technologies. The ideal candidate will have strong expertise in Large Language Models (LLMs), Generative AI (GenAI), and Retrieval-Augmented Generation (RAG) systems, with the ability to integrate AI models with enterprise data and business workflows.

This role requires a strong software engineering background combined with hands-on experience in developing scalable AI-driven applications, optimizing model performance, and delivering production-ready solutions.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI technologies.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines integrated with enterprise data sources.
• Develop effective prompt engineering strategies to improve AI output quality, consistency, and reliability.
• Prepare and process structured and unstructured datasets for AI model consumption, including data cleaning, chunking, and embedding generation.
• Integrate AI systems with internal platforms, APIs, and business applications.
• Work with vector databases such as Pinecone or FAISS for semantic search and knowledge retrieval.
• Evaluate model performance and continuously improve solution accuracy, latency, and scalability.
• Collaborate with cross-functional teams to identify AI use cases and deliver business-driven solutions.
• Stay updated with the latest advancements in AI, LLMs, and GenAI technologies.

Requirements

• Bachelor’s degree in computer science, Software Engineering, AI, or a related field.
• Minimum 4 years of software development experience.
• Recent hands-on experience in Artificial Intelligence, particularly in LLM and GenAI applications.
• Strong understanding of Large Language Models (LLMs) and their practical applications.
• Proven experience in designing and implementing Generative AI solutions.
• Strong experience in Prompt Engineering.
• Hands-on experience building RAG solutions.
• Strong proficiency in Python.
• Experience in data preparation for AI systems (Cleaning, Chunking, Embedding).
• Experience working with vector databases such as Pinecone or FAISS.
• Familiarity with Fine-Tuning techniques is a strong plus.