全职 Artificial Intelligence Engineer 工作, 薪水, Agensi Pekerjaan Eternity Federal Territory 公司招聘中 - Ricebowl

Job Description – Artificial Intelligence Engineer

(Full Stack | AI System Architect)

Role Summary

Designs, develops, and deploys production-grade AI systems, including multi-agent platforms, real-time computer vision solutions, and full-stack enterprise applications. Works across the entire AI lifecycle—from architecture and orchestration to deployment and optimization—delivering scalable, business-impactful solutions.

Key Responsibilities

• Architect and deploy multi-agent orchestration systems to automate complex workflows and convert raw data into actionable business intelligence.
• Build and ship end-to-end AI web applications, including both internal tools and client-facing products, with integrated frontend, backend, and AI components.
• Develop real-time vision and voice AI microservices for live video and audio streaming infrastructure.
• Design and implement automated quality assurance systems using streaming speech-to-text and multi-agent evaluation frameworks.
• Engineer full-stack data validation and rule-management platforms using FastAPI, Next.js, and Docker, deployed on cloud infrastructure.
• Deploy secure, self-hosted multi-model AI chat workspaces with token tracking, billing controls, and role-based access management.
• Build AI-powered voice agents with session memory and dynamic response handling for enterprise customer interaction workflows.
• Develop document comparison and reconciliation automation tools using AI vision models for invoice and folio verification.
• Lead research and development on multi-agent orchestration patterns and knowledge-base architectures for scalable AI deployments.
• Build speech-based and document intelligence systems integrating speech-to-text, conversational AI, and document extraction pipelines.
• Design multi-agent and RAG-based architectures for enterprise automation and intelligent customer service platforms.
• Collaborate with product and machine learning teams to optimize latency, model accuracy, and cost efficiency in production-grade AI systems.

Ideal Candidate

• Proven track record in building and deploying production AI systems across multi-agent, vision, voice, and full-stack domains.
• Deep understanding of current AI market trends and the ability to align technical execution with business value.
• Strong cross-functional collaboration skills, working effectively with product and ML teams.
• Hands-on experience with cloud AI ecosystems and production-grade deployments.
• Passion for continuous building, shipping, and staying ahead in the fast-evolving AI landscape.

Technical Skills

Frontend & Backend

• Next.js, React.js, Flask, FastAPI, Docker

AI & Machine Learning

• Agentic AI Development, Retrieval-Augmented Generation (RAG), NLP, Large Language Models (LLMs), Computer Vision, OCR

Cloud Platforms

• Cloud-native AI services, serverless architectures, containerized deployments

Architecture

• Multi-agent orchestration, knowledge-base architectures, microservices