AI Architect

Systems Limited; Malaysia; On-site; MYR 180,000 - 360,000; Full time

Job summary

Systems Limited is seeking a hands-on AI Architect to lead enterprise GenAI initiatives from concept to production. You will design, build, and deliver scalable AI solutions while working closely with business stakeholders.

The role requires expertise in LLMs, RAG, Azure AI services, governance, and evaluation frameworks, with a track record of deploying AI in cloud environments and mentoring engineers.

Qualifications

• 8+ years of AI/ML engineering and solution architecture.
• 3+ years hands-on experience building production-grade GenAI and LLM apps.
• Strong Python, FastAPI, Azure AI services, and NLP fundamentals.
• Experience with AI agents and evaluation metrics.
• Experience deploying AI on Azure with CI/CD and hybrid architectures.
• Bachelor's in CS/AI/Data Science; Master’s preferred.

Responsibilities

• Lead end-to-end design, development, and deployment of AI and GenAI solutions.
• Architect scalable, secure AI systems using Azure AI services.
• Collaborate with business and client stakeholders to translate requirements into AI solutions.
• Build and optimize LLM-powered applications, RAG pipelines, APIs, and workflows.
• Mentor junior engineers and ensure solution quality.
• Implement AI evaluation, observability, guardrails, and responsible AI practices.
• Deploy AI applications with CI/CD, monitoring, and cloud infra.

Skills

AI/ML engineering

Solution architecture

Python

FastAPI

Azure AI services

RAG

LLM orchestration

NLP

Prompt engineering

AI governance

Education

Bachelor's degree in CS/AI/Data Science

Master's degree preferred

Tools

LangGraph

AutoGen

Semantic Kernel

CrewAI

LangSmith

Langfuse

Azure AI Foundry

HuggingFace

Vector databases

Job description

We are seeking a hands‑on AI Architect with extensive experience in Generative AI, Machine Learning, and Solution Architecture to design, build, and deliver enterprise‑grade AI solutions. The ideal candidate will lead multiple AI initiatives from concept to production, work closely with business stakeholders, and remain actively involved in implementation. This role requires expertise in LLMs, RAG architectures, Azure AI services, AI governance, evaluation frameworks, and scalable cloud‑based deployments.

Key Responsibilities:

• Lead the end‑to‑end design, development, and deployment of AI and GenAI solutions.
• Architect scalable, secure, and high‑performance AI systems using Azure AI services.
• Collaborate with business and client stakeholders to translate requirements into AI solutions.
• Build and optimize LLM‑powered applications, RAG pipelines, APIs, and AI workflows.
• Design AI solutions for document intelligence, summarization, classification, Q&A, and automation.
• Implement AI evaluation, observability, guardrails, and responsible AI practices.
• Optimize production AI systems for performance, latency, cost, and accuracy.
• Deploy AI applications using CI/CD, monitoring, logging, and cloud infrastructure.
• Develop traditional ML models where required and mentor junior engineers while ensuring solution quality.

Qualifications:

• 8+ years of experience in AI/ML engineering and solution architecture.
• 3+ years of hands‑on experience building production‑grade GenAI and LLM applications.
• Strong expertise in Python, FastAPI, Azure AI services, RAG, embeddings, vector databases, and LLM orchestration frameworks.
• Experience with AI agents (LangGraph, AutoGen, Semantic Kernel, CrewAI), AI evaluation (RAGAS, BLEU, Precision, Recall, F1), and observability tools (LangSmith, Langfuse, Azure AI Foundry).
• Solid understanding of NLP, prompt engineering, responsible AI, guardrails, model evaluation, and AI governance.
• Experience deploying AI solutions on Azure with CI/CD, monitoring, and hybrid cloud/on‑premise architectures.
• Experience with HuggingFace, open‑source LLMs, and enterprise AI deployments.
• Bachelor's degree in Computer Science, AI, Data Science, or a related field (Master's preferred).

Preferred:

• Experience with open‑source LLMs (LLaMA, Mistral, Qwen, DeepSeek).
• Exposure to AWS Bedrock or GCP Vertex AI.
• Experience with multilingual NLP (especially Arabic).
• Microsoft Azure certifications (AI-102, DP-100, AZ-305).