AI Developer _ Vector Database & Generative AI

Centraprise, Corp.; Pennington (NJ); On-site; USD 120,000 - 180,000; Full time

Job summary

Centraprise, Corp. seeks an experienced AI Developer to design and optimize AI-powered applications using vector databases and RAG approaches in Pennington, NJ. You will integrate AI models with enterprise systems and ensure high-quality retrieval and responses.

The role emphasizes building scalable AI-driven solutions, collaborating with cross-functional teams, and continuously improving AI applications through testing and monitoring.

Qualifications

• Hands-on experience with vector databases and semantic search.
• Experience building RAG-based architectures using LLMs and embeddings.
• Familiarity with embedding models and large language models.
• Proficiency in VS Code and API integration for AI apps.
• Knowledge of Generative AI concepts and LLM tooling.

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.

Skills

Vector Databases

RAG architectures

Embedding Models

Semantic Search

Prompt Engineering

VS Code

API Integration

Generative AI

LLMs

Tools

Pinecone

Weaviate

Milvus

ChromaDB

Azure AI Search

VS Code

Job description

Job title: AI Developer _ Vector Database & Generative AI

Job Location: Pennington, NJ

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)