Agentic AI Engineer — Production Operations & RAG Pipelines

Centraprise, Corp.; México; On-site; MXN 900,000 - 1,300,000; Full time

Job summary

Centraprise, Corp. seeks an AI-Native Engineer to design, develop, deploy, and operate enterprise Generative and Agentic AI solutions. The role emphasizes production operations, including monitoring, incident response, data migrations, and continuous evaluation in a Google Cloud environment.

The ideal candidate will work with Google Gemini, Vertex AI, BigQuery, RAG pipelines, and vector databases, bringing strong Python skills and a track record of end-to-end AI system ownership in production.

Qualifications

• Hands-on experience designing, deploying, and operating production AI systems.
• Strong Python development skills and software engineering fundamentals.
• Experience with RAG pipelines, vector databases, and observability tools.
• Ability to manage end-to-end lifecycle from development to production support.

Responsibilities

• Design, deploy, and maintain production-grade Agentic AI and Multi-Agent systems.
• Develop orchestration, tools, and API integrations for agents.
• Build reliable execution workflows with retries, error handling, and recovery.
• Monitor production AI systems and perform RCA on incidents.
• Maintain observability and data pipelines for end-to-end AI workloads.
• Lead data migrations, VDB updates, and QA for AI knowledge sources.
• Ensure security, compliance, and deployment safety in production.

Skills

Python development

Debugging

Software engineering

Incident management

Production ownership

Tools

Google Gemini

Google ADK

Vertex AI

LangChain

LlamaIndex

REST APIs

gRPC

Docker

Git

OpenTelemetry

Prometheus

Grafana

Datadog

Chroma

Pinecone

Vector databases

BigQuery

Job description

Centraprise, Corp. seeks an AI-Native Engineer to design, develop, deploy, and operate enterprise Generative and Agentic AI solutions. The role emphasizes production operations, including monitoring, incident response, data migrations, and continuous evaluation in a Google Cloud environment.

The ideal candidate will work with Google Gemini, Vertex AI, BigQuery, RAG pipelines, and vector databases, bringing strong Python skills and a track record of end-to-end AI system ownership in production.