Python GCP AI Engineer (AI Chatbot Development) - 100% Remote

Location: Brazil (Remote)

Duration: 12+ Months

Rate: DOE

Job Summary

We are seeking a highly skilled Python GCP AI Engineer with proven experience in designing, developing, and deploying AI-powered chatbot solutions on Google Cloud Platform (GCP). This is not a traditional DevOps or Cloud Infrastructure role. The ideal candidate must have hands-on experience working on Generative AI projects using the GCP AI ecosystem, including Gemini models and Vertex AI.

Mandatory Skills

  • Strong Python development experience.
  • Hands-on experience building AI Chatbots on Google Cloud Platform (GCP).
  • Experience with Vertex AI, Gemini Models, and GCP AI services.
  • Experience implementing Retrieval-Augmented Generation (RAG) architectures.
  • Knowledge of Prompt Engineering, prompt optimization, and prompt evaluation.
  • Experience integrating LLMs with enterprise applications using REST APIs.
  • Strong understanding of Vector Databases, embeddings, and semantic search.
  • Experience implementing AI guardrails, content safety, and responsible AI practices.
  • Knowledge of Google Cloud services such as Cloud Run, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, and IAM.
  • Experience monitoring AI applications, token consumption, latency, and cost optimization.

Roles & Responsibilities

  • Design, develop, and deploy enterprise AI chatbot solutions using the GCP AI technology stack.
  • Build and maintain Generative AI applications utilizing Vertex AI and Gemini foundation models.
  • Develop scalable backend services in Python for AI-powered applications.
  • Implement Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources.
  • Optimize prompts, retrieval strategies, and AI guardrails to improve chatbot performance.
  • Monitor token usage and drive token cost optimization initiatives.
  • Lead incident triage, root cause analysis, and release rollback decisions for AI applications.
  • Own end-to-end technical delivery, architecture, deployment, and production support.
  • Maintain operational runbooks, knowledge base documentation, and governance standards.
  • Conduct weekly service reviews, monthly governance meetings, and risk reporting.
  • Collaborate with business stakeholders to continuously improve AI chatbot capabilities.