AI Engineer (GenAI / RAG / LangGraph / Python)

Unison Group; Kuala Lumpur; On-site; MYR 180,000 - 300,000; Full time

Job summary

Unison Group is seeking a highly skilled AI Engineer to design, build, and deploy enterprise-grade Generative AI applications powered by LLMs and modern AI frameworks.

You will craft intelligent AI agents, orchestrate LangGraph workflows, and integrate enterprise knowledge bases with Elastic Knowledge, ensuring scalable GenAI solutions for business use cases.

Qualifications

• Experience designing enterprise-grade GenAI applications.
• Capable of building intelligent AI agents and multi-agent workflows.
• Experience integrating enterprise knowledge bases.
• Strong Python proficiency.
• Knowledge of governance and security best practices.

Responsibilities

• Design and develop enterprise Generative AI applications using Python.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval.
• Develop AI workflows and multi-agent systems using LangGraph.
• Create effective prompts and prompt templates for various LLM use cases.
• Integrate enterprise knowledge repositories using Elastic Knowledge or Elasticsearch-based knowledge systems.
• Develop intelligent AI assistants, chatbots, and agentic AI solutions.
• Connect LLMs with enterprise APIs, databases, and document repositories.
• Optimize retrieval quality, context management, and response accuracy.
• Implement vector search and semantic search capabilities.
• Evaluate, fine-tune, and monitor LLM performance.
• Collaborate with business stakeholders to understand AI use cases and translate them into technical solutions.
• Follow AI governance, security, and responsible AI best practices.

Skills

Python programming

LangGraph

Retrieval-Augmented Generation

Prompt Engineering

Generative AI

LLMs integration

REST APIs

Microservices

LangChain ecosystem

Multi-agent workflows

Tools

Elasticsearch

LangChain

Pinecone

Chroma

FAISS

Weaviate

Milvus

OpenAI / Azure OpenAI

Job description

Description

We are looking for a highly skilledAI Engineerwith strong expertise inGenerative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), LangGraph, Elastic Knowledge, and Python. The ideal candidate should have experience designing, developing, and deploying enterprise-grade AI applications powered by Large Language Models (LLMs) and modern AI frameworks.

The candidate should be capable of building intelligent AI agents, orchestrating complex workflows using LangGraph, integrating enterprise knowledge bases, and developing scalable GenAI solutions for business use cases.

Key Responsibilities

• Design and develop enterprise Generative AI applications using Python.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval.
• Develop AI workflows and multi-agent systems using LangGraph.
• Create effective prompts and prompt templates for various LLM use cases.
• Integrate enterprise knowledge repositories using Elastic Knowledge or Elasticsearch-based knowledge systems.
• Develop intelligent AI assistants, chatbots, and agentic AI solutions.
• Connect LLMs with enterprise APIs, databases, and document repositories.
• Optimize retrieval quality, context management, and response accuracy.
• Implement vector search and semantic search capabilities.
• Evaluate, fine-tune, and monitor LLM performance.
• Collaborate with business stakeholders to understand AI use cases and translate them into technical solutions.
• Follow AI governance, security, and responsible AI best practices.

Required Skills

• Strong Python programming experience.
• Hands-on experience withLangGraph.
• Strong knowledge ofRetrieval-Augmented Generation (RAG).
• Experience withPrompt Engineeringand prompt optimization.
• Experience developing applications usingGenerative AItechnologies.
• Knowledge ofElastic Knowledge / Elasticsearchfor enterprise search and knowledge retrieval.
• Experience withLangChainecosystem.
• Experience integrating OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLMs.
• Knowledge of vector databases such as Pinecone, Chroma, FAISS, Weaviate, or Milvus.
• Experience building AI agents and multi-step workflows.
• Strong understanding of REST APIs and microservices.
• Familiarity with Git, Docker, and CI/CD pipelines.