AI Native Engineer: GenAI & Multi-Agent Systems on GCP

XChange Software Inc

México

On-site

MXN 900,000 - 1,300,000

Full time

5 days ago
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Job summary

XChange Software Inc. is seeking AI Native Engineers to design, deploy, and support enterprise AI applications, including Generative AI, Agentic AI, and Multi-Agent systems.

The role focuses on production-grade AI delivery on Google Cloud Platform using Vertex AI, LangChain, and RAG workflows. You will build AI workflows, integrate APIs, monitor performance, and ensure reliability across data pipelines, BigQuery, and vector stores, while embracing continuous improvement and robust testing

Qualifications

  • Experience in AI engineering, production support, and data pipelines.
  • Strong hands-on knowledge of Google Cloud Platform (GCP).
  • Ability to develop, deploy, and monitor AI solutions.

Responsibilities

  • Develop and maintain AI agents and multi-agent applications.
  • Work with Gemini, Google ADK, Vertex AI, and RAG solutions.
  • Build and manage AI workflows, API integrations, and automation.
  • Monitor production AI applications and resolve technical issues.
  • Perform troubleshooting, debugging, and Root Cause Analysis (RCA).
  • Manage data migration, ETL/ELT pipelines, and BigQuery.
  • Maintain Vector Databases and RAG pipelines.
  • Monitor AI performance, data quality, and system reliability.
  • Perform testing, deployment, and continuous improvements.

Skills

Generative AI
Agentic AI
Multi-Agent Systems
Gemini

Tools

Google ADK
Vertex AI
LangChain
LlamaIndex
Python
REST APIs
gRPC
Docker
Git
CI/CD
Automated Testing

Job description

XChange Software Inc. is seeking AI Native Engineers to design, deploy, and support enterprise AI applications, including Generative AI, Agentic AI, and Multi-Agent systems.

The role focuses on production-grade AI delivery on Google Cloud Platform using Vertex AI, LangChain, and RAG workflows. You will build AI workflows, integrate APIs, monitor performance, and ensure reliability across data pipelines, BigQuery, and vector stores, while embracing continuous improvement and robust testing

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