Job Description

JOB DUTIES AND RESPONSIBILITIES

Integrations & Workflow Automation

Build and maintain integrations between chatbot systems and workflow platforms (Dify, n8n, LangGraph, LangChain, LangFlow, or AnythingLLM). Implement automation triggers, task orchestration, and API routing for smooth AI workflows.
LLM & Agentic AI Development

Implement prompt engineering, RAG pipelines, multi-agent or autonomous agent frameworks, and Model Context Protocol (MCP) for context-aware, agentic AI workflows. Prepare vector stores / knowledge bases and generate embeddings for retrieval-augmented generation (RAG) and contextual model queries. Preprocess and integrate multimodal data (text, image or tabular) into AI workflows.
Backend & API Engineering

Design and expose ML services via Flask, FastAPI or any REST APIs for microservice architectures. Use Docker/ Kubernetes, CI/CD pipelines, and Git for deployment and lifecycle management.
Model Monitoring & Governance

Monitor deployed models for performance drift, latency, and system reliability. Ensure responsible AI practices: privacy compliance, bias mitigation, and transparent model behavior.
Collaboration & Agile Practices

Collaborate with software engineers, product managers, and domain experts to translate requirements into AI solutions. Work within Agile & Scrum processes to deliver iterative and incremental value.

JOB REQUIREMENTS

Education

Bachelor's degree in Computer Science, AI/ML, Software Engineering, Data Science, or a related field. Master's degree is a plus but not mandatory.
Experience

1-3 years in software development, AI/ML engineering or backend integration. Hands-on experience with LLM tools, RAG pipelines or embedding-based search. Exposure to MLOps or AI deployment pipelines is a plus.
Technical Skills

Programming

: Python

AI/ML Tools

: LangChain, LangGraph, LangFlow, Dify, AnythingLLM, HuggingFace, OpenAI API

Vector Databases

: FAISS, Pinecone, Milvus for vector store preparation and embeddings

Embedding Models

: OpenAI Embeddings, HuggingFace models, other vectorization frameworks

Agentic AI & MCP

: Multi-agent OR autonomous agents with Model Context Protocol (MCP) integration

Backend APIs

: Flask, FastAPI (REST APIs)

DevOps & Deployment

: Docker, Kubernetes, CI/CD pipelines, Git version control

Data Processing

: Structured, unstructured, multimodal data workflows

Model Evaluation

: Metrics for accuracy, latency, hallucination rate, and production readiness.
Job Types: Full-time, Permanent

Pay: RM3,000.00 - RM6,000.00 per month

Benefits:

Health insurance Opportunities for promotion Professional development
Application Question(s):

Do you have experience of AI Model testing?
Experience:

Quality assurance: 1 year (Preferred)
Work Location: In person