Job Description

Key Responsibilities

Design and implement backend services/APIs using

Python

(e.g. with

FastAPI

or similar frameworks) to support AI agents. Build and maintain

RAG pipelines

: document ingestion (manuals, notes), embedding computation, vector indexing and search (vector DB or PG-vector), retrieval, ranking, LLM-based answer generation. Integrate with LLM providers (e.g., OpenAI, Gemini, open-source LLMs) in a modular, provider-agnostic way. Maintain prompt templates, tool abstraction, and agent orchestration. Implement

memory / state management

for chatbots (session memory, optional long-term memory), user history, and context persistence. Develop and maintain

tool orchestration logic

(agent ? tool graph ? conditional routing / fan-out), ensuring clean, modular, testable architecture. Design and manage data storage: relational data (user profiles, chat history, metadata) in PostgreSQL; NoSQL database; semantic data (embeddings, vector indices) via vector store (or PG-vector). Design, train, and deploy machine learning models (e.g., supervised/unsupervised, deep learning) with strong understanding of model evaluation, feature engineering, and MLOps best practices. Ensure robustness, reliability, and maintainability: error handling, logging, monitoring, performance profiling, and test coverage. Collaborate with product, operations, and other stakeholders to translate business needs into technical workflows and deliver production-ready features.

Required Skills & Experience

Strong proficiency in

Python

(3.9+) with experience in backend development. Experience building APIs/web services using

FastAPI, Flask, or similar

frameworks. Understanding of

LLM integration

, prompt engineering, and LLM-based generation workflows (RAG, retrieval + generation, contextual LLM usage). Familiarity with

vector search / embeddings / vector databases

-- able to work with vector stores (pgvector, Chroma, FAISS, Qdrant, etc.) or relational-vector hybrid storage. Solid knowledge of

relational databases

(PostgreSQL or similar), schema design, indexing, and data modeling. Good software engineering practices: modular code design, version control (Git), documentation, testing, and code reviews. Ability to design and maintain asynchronous workflows, background tasks, and efficient data pipelines (embedding generation, indexing, retrieval, memory). Problem-solving mindset -- ability to debug complex issues, design fallback logic (e.g., hallucination detection, fallback LLM responses), and ensure system reliability.

Qualifications

Bachelor's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, or related field (or equivalent experience). Fresh graduates or candidates with 1-2 years of AI-related software development experience are welcome.
Job Types: Full-time, Fresh graduate

Pay: RM3,800.00 - RM5,000.00 per month

Benefits:

Flexible schedule Opportunities for promotion Professional development Work from home
Work Location: Hybrid remote in Kuala Lumpur