AI/RAG engineer

CoinMarketCap; Penang; On-site; MYR 60,000 - 90,000; Full time

Job summary

A leading technology company is seeking an AI Systems Developer to build innovative AI search agents and RAG pipelines. This role requires expertise in Python, machine learning frameworks, and a strong understanding of vector search technologies. The ideal candidate will have a proven track record in developing AI systems and optimizing production environments, contributing to cutting-edge projects in a dynamic team.

Qualifications

• 3+ years of experience in developing AI systems with a focus on RAG.
• Proven track record in building and optimizing end-to-end RAG pipelines.
• Hands-on experience with OpenSearch or similar vector search technologies.

Responsibilities

• Building AI search agents and end-to-end RAG pipelines.
• Operating and monitoring vector/hybrid indexes in production environments.
• Automate evaluation using synthetic QA and model-critique loops.

Skills

Python

Machine Learning

Data Ingestion

Hybrid Vector Search

Monitoring Production Environments

Education

Bachelor’s or Master’s degree in Computer Science

Bachelor’s or Master’s degree in Artificial Intelligence

Bachelor’s or Master’s degree in Machine Learning

Tools

OpenSearch

PyTorch

TensorFlow

LangGraph

Dify

CrewAI

Job description

Job Responsibilities

• Building AI search agents- including ReAct, planning, and multi-agent architectures via custom implementation or frameworks like LangGraph, Dify, or CrewAI
• Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using Opensearch
• Operating and monitoring vector/hybrid indexes (e.g. OpenSearch) in production environments
• Implement grounding and citation to link generated answers back to their exact source passages
• Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to continuously measure accuracy and detect drift
• Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale
  
  
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
• 3+ years of experience in developing AI systems, with a focus on retrieval-augmented generation (RAG)
• Proven track record in building and optimizing end-to-end RAG pipelines
• Experience with AI search agent development using frameworks like ReAct, LangGraph, Dify, or CrewAI
• Hands-on experience with OpenSearch or similar vector search technologies
• Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow)
• Strong understanding of data ingestion, chunking, embeddings, and hybrid vector search techniques
• Experience with monitoring and managing production environments
• Knowledge of grounding and citation techniques in AI-generated content
• Familiarity with synthetic QA datasets and evaluation metrics