Agentic AI Engineer (MY) at Oxydata Software

Petaling Jaya, Selangor, Malaysia -

Full Time

Start Date

Immediate

Expiry Date

18 Sep, 26

Salary

0.0

Posted On

20 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

LangGraph, CrewAI, N8N, Python, FastAPI, GPT Vision, RAG, Prompt Engineering, Vector Search, LLM APIs, Linux Administration, Git, Multi-Agent Orchestration, Function Calling, Model Context Protocol, Backend Development

Industry

IT Services and IT Consulting

Description

Oxydata Software Sdn Bhd Location: Petaling Jaya, Selangor Work Mode: Hybrid Contract Type: Full-time Employment Eligibility: Malaysian Only About Oxydata Oxydata Software Sdn Bhd is a Malaysia Digital-certified AI and data engineering company founded in 2006. We design and deploy production AI systems for enterprise clients across financial services,human resource, energy, and telecommunications. We are now expanding our Agentic AI practice — building autonomous, multi-step AI workflows that go beyond single-prompt responses to deliver real business process automation. The Role We are looking for an Agentic AI Engineer to lead the design and implementation of multi-agent AI systems across our product and client delivery portfolio. This role is not about building dashboards — it is about architecting autonomous AI workflows that reason, plan, use tools, and execute multi-step tasks with minimal human intervention. You will work in a small, senior team using AI-assisted development tools as standard practice. What You'll Build Multi-Agent Orchestration Design and implement multi-agent pipelines using LangGraph and CrewAI Agent role definition, task decomposition, inter-agent communication, and state management Supervisor/worker agent architectures for complex, multi-step reasoning tasks Workflow Automation Build production automation workflows using N8N — triggers, conditionals, API calls, data transforms Integrate AI agents into broader business process automation pipelines Design human-in-the-loop checkpoints for workflows requiring approval or escalation Tool Use & Function Calling Implement tool-calling agents with access to APIs, databases, search, and file systems Build custom tools and MCP (Model Context Protocol) servers for agent consumption Memory management — short-term, long-term, and episodic memory for persistent agents Multimodal AI GPT Vision integration for document parsing, screenshot analysis, and visual data extraction Multimodal pipelines combining text, image, and structured data inputs RAG & Knowledge Retrieval Integrate RAG pipelines as retrieval tools within agentic workflows Vector search (pgvector, Pinecone, or similar) for agent knowledge grounding Prompt engineering for agent personas, reasoning chains, and output formatting Production Deployment Deploy agentic systems on self-hosted VPS infrastructure Observability, logging, and failure handling for long-running agent workflows API endpoints (FastAPI) exposing agent capabilities to frontend and external systems Must-Haves Education: Bachelor's in Computer Science, Software Engineering, AI, or related field Experience: 1–4 years in AI/ML engineering with hands-on production experience in agentic or LLM-based systems Agentic Frameworks: Demonstrated production experience with LangGraph and/or CrewAI Workflow Automation: Hands-on N8N workflow design and deployment Multimodal AI: GPT Vision or equivalent for image/document understanding Language: Python (primary); comfortable reading JavaScript LLM APIs: OpenAI API, Claude API, function calling, tool use, structured outputs Prompt Engineering: System prompts, chain-of-thought, ReAct patterns, output formatting RAG Fundamentals: Embeddings, vector search, retrieval grounding — as agent tools Backend: FastAPI for exposing agent capabilities as APIs DevOps: Git, VPS/cloud deployment, basic Linux administration, error handling for async workflows Nice-to-Haves LangChain or LlamaIndex for knowledge-base construction MCP (Model Context Protocol) server development Experience with AI-assisted development tools (Cursor, GitHub Copilot) Docker for containerised agent deployment CI/CD pipelines for agent workflow testing and deployment React.js — basic frontend ability to build simple agent UIs or dashboards Experience with structured output validation (Pydantic, instructor library) What We Offer Be among the first engineers in Malaysia building production-grade Agentic AI systems Work on real client deployments — not internal tools or proofs of concept AI-first development culture — Cursor and Claude are standard tools, not novelties Small, senior team — high ownership, direct impact, no bureaucracy Competitive compensation commensurate with experience How to Apply Submit your CV via our careers page: https://oxydata.ai/careers #AgenticAI #LangGraph #CrewAI #N8N #GPTVision #MultiAgent #AIEngineer #GenerativeAI #Malaysia #Hiring #Oxydata

Responsibilities

Lead the design and implementation of autonomous multi-agent AI systems and production automation workflows. Architect systems that reason, plan, and execute multi-step tasks using tools like LangGraph, CrewAI, and N8N.