RAG Engineer: Enterprise AI Knowledge Architect

Onemci; Philippines; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Onemci in the Philippines is seeking a skilled RAG Engineer to design Retrieval-Augmented Generation systems that fuse large language models with enterprise data. You will build ingestion, indexing and retrieval pipelines and create scalable knowledge repositories.

The role focuses on vector search, data optimization, AI integration, APIs, and secure, governed deployments. You will work with AI engineers and product teams to deliver reliable knowledge retrieval, monitor performance and ensure

Qualifications

• Bachelor's degree in a technical field.
• 3+ years in software/AI engineering or information retrieval.
• Proficiency in Python and production-grade app development.
• Experience with APIs, microservices, or cloud-native apps.
• Solid understanding of LLMs and Generative AI concepts.
• Experience designing Retrieval-Augmented Generation solutions.
• Knowledge of embeddings and semantic search techniques.
• Experience with structured and unstructured data ingestion, indexing, retrieval.

Responsibilities

• Design and maintain RAG solutions for accurate, context-aware responses.
• Build document ingestion, indexing, and retrieval pipelines.
• Develop enterprise knowledge repositories and search frameworks.
• Implement semantic search across data sources.
• Design scalable architectures for AI-powered knowledge retrieval.
• Optimize vector search performance and embedding pipelines.
• Integrate retrieval systems with AI applications and APIs.
• Collaborate with AI engineers and product teams on solution design.

Skills

Python

LLMs

Retrieval-Augmented Generation

APIs

Microservices

Cloud platforms

Education

Bachelor's Degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Software Engineering, or related field

Tools

APIs

Vector databases

Embedding pipelines

Cloud services

Job description

Onemci in the Philippines is seeking a skilled RAG Engineer to design Retrieval-Augmented Generation systems that fuse large language models with enterprise data. You will build ingestion, indexing and retrieval pipelines and create scalable knowledge repositories.

The role focuses on vector search, data optimization, AI integration, APIs, and secure, governed deployments. You will work with AI engineers and product teams to deliver reliable knowledge retrieval, monitor performance and ensure