Enterprise AI Solutions Architect

ABeam Consulting (Singapore); Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

ABeam Consulting seeks a seasoned AI Engineer to design, develop, test, and deploy enterprise-grade AI applications and agents in Malaysia. You will identify use cases with business users, translate requirements into scalable AI designs, and build robust AI components using LLMs, RAG, and agentic frameworks.

You will integrate AI solutions with enterprise data, ensure security and governance, and deliver production-ready workflows with LangChain, MCP, and APIs.

Qualifications

• Hands-on experience in AI Engineering, Generative AI, or Agentic AI development.
• Experience designing solutions using LLMs and RAG.
• Proficient in Python and API/backend development.
• Familiar with LangChain/LangGraph or similar.
• Experience with cloud AI services (Azure OpenAI, Vertex AI).

Responsibilities

• Work with business users and stakeholders to identify, assess, and prioritize potential AI and Agentic AI use cases.
• Understand business processes, pain points, data availability, and system constraints, and translate them into appropriate AI solution designs.
• Design, develop, test, and deploy enterprise-grade AI applications and AI agents.
• Develop AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
• Design and implement single-agent and multi-agent workflows, including agent communication, task delegation, decision logic, memory, and tool orchestration.
• Develop orchestration workflows using technologies such as LangChain, LangGraph, MCP, and similar agent frameworks.
• Integrate AI agents with enterprise applications, databases, APIs, document repositories, and external tools.
• Develop robust backend services and APIs using Python and frameworks such as FastAPI.
• Design and implement RAG pipelines covering document ingestion, chunking, embedding, retrieval, hybrid search, reranking, prompt construction, and response generation.
• Build reusable AI components, agent tools, APIs, connectors, and services to accelerate future AI implementations.
• Develop POCs rapidly and work with stakeholders to validate business feasibility, technical feasibility, and expected value.
• Industrialize successful POCs into scalable and maintainable production solutions.
• Implement appropriate security, access control, guardrails, governance, observability, and monitoring for enterprise AI applications.
• Define evaluation frameworks and success metrics to assess AI agent performance, including response quality, accuracy, reliability, latency, token consumption, and business outcomes.
• Establish feedback loops and continuously improve AI agent performance based on evaluation results and user feedback.
• Troubleshoot and optimize AI applications, including prompts, retrieval quality, agent workflows, model selection, and system performance.
• Collaborate with infrastructure, security, application, data, and architecture teams to support successful enterprise deployment.
• Communicate AI concepts, solution architecture, limitations, risks, and recommendations clearly to both technical and non-technical stakeholders.
• Prepare solution documentation, architecture designs, implementation plans, technical specifications, test scenarios, and operational documentation.
• Provide knowledge transfer and technical guidance to client teams to support sustainable adoption of AI solutions.

Skills

AI Engineering

Generative AI

Agentic AI

Python

LLMs

RAG Architecture

LangChain

LangGraph

MCP

APIs & Backend

Cloud Platforms

Azure OpenAI

Vertex AI

Multi-agent Workflows

Education

Degree in Computer Science or related discipline

Tools

LangChain

LangGraph

MCP

Google Vertex AI

Google Antigravity

Microsoft Copilot

Copilot Studio

Foundry

Job description

ABeam Consulting seeks a seasoned AI Engineer to design, develop, test, and deploy enterprise-grade AI applications and agents in Malaysia. You will identify use cases with business users, translate requirements into scalable AI designs, and build robust AI components using LLMs, RAG, and agentic frameworks.

You will integrate AI solutions with enterprise data, ensure security and governance, and deliver production-ready workflows with LangChain, MCP, and APIs.