GenAI Engineer: Mastering RAG, LangGraph & Python

Unison Group

Singapore

Presencial

SGD 120.000 - 180.000

Jornada completa

14 días+

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Descripción de la vacante

Unison Group in Singapore is seeking a highly skilled AI Engineer to design, develop and deploy enterprise-grade AI applications powered by Large Language Models. You will work with Generative AI, Prompt Engineering, Retrieval-Augmented Generation, LangGraph, Elastic Knowledge, and Python.

You will build AI agents and multi-step workflows, integrate enterprise knowledge bases, optimize prompts and vectors, connect LLMs to APIs and data stores, and ensure governance and security best practices.

Formación

  • Strong Python programming experience.
  • Hands-on experience with LangGraph and RAG pipelines.
  • Expertise in prompt engineering and GenAI technologies.
  • Experience integrating OpenAI/Azure OpenAI and other LLMs.

Responsabilidades

  • Design and develop enterprise Generative AI applications using Python.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines.
  • Develop AI workflows and multi-agent systems using LangGraph.
  • Create prompts and templates for various LLM use cases.
  • Integrate enterprise knowledge repositories using Elastic Knowledge.
  • Develop AI assistants and agentic AI solutions.
  • Connect LLMs with enterprise APIs and data stores.
  • Optimize retrieval quality, context management and answer accuracy.
  • Evaluate, fine-tune and monitor LLM performance.

Conocimientos

Python
LangGraph
RAG
Prompt Engineering
Generative AI
LangChain
LLMs
APIs
Vector databases

Herramientas

Elasticsearch

Descripción del empleo

Unison Group in Singapore is seeking a highly skilled AI Engineer to design, develop and deploy enterprise-grade AI applications powered by Large Language Models. You will work with Generative AI, Prompt Engineering, Retrieval-Augmented Generation, LangGraph, Elastic Knowledge, and Python.

You will build AI agents and multi-step workflows, integrate enterprise knowledge bases, optimize prompts and vectors, connect LLMs to APIs and data stores, and ensure governance and security best practices.

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