AI Developer _ Vector Database & Generative AI

Roles & Responsibilities

Highly skilled AI Developer with hands-on expertise in Vector Databases, strong knowledge of AI Models and Large Language Models (LLMs), and proficiency in Visual Studio Code (VS Code). The candidate will design, develop, and optimize AI-powered applications, build Retrieval-Augmented Generation (RAG) solutions, manage vector-based data retrieval systems, and integrate AI models with enterprise applications.

Key Responsibilities

• Design and implement vector database solutions for semantic search and AI applications.
• Develop RAG-based architectures using LLMs and embedding models.
• Integrate AI models with enterprise systems and data sources.
• Optimize vector indexing, retrieval performance, and AI response quality.
• Collaborate with cross-functional teams to build scalable AI-driven solutions.
• Perform testing, monitoring, and continuous improvement of AI applications.

Technical/Functional Skills

• Primary Skill: Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB, Azure AI Search), Retrieval Augmented Generation (RAG), Embedding Models and Semantic Search, Prompt Engineering, Visual Studio
• Code (VS Code), API Integration and AI Application Development, Generative AI and Large Language Models (GPT, Llama, Claude, Gemini)
• Secondary: Python, JavaScript, TypeScript, AI Governance, Responsible AI, and Security, Git, GitHub, Microsoft 365 Ecosystem