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RemoteListed Jul 18, 2026

AI Engineer

Metova

  • AI-Engineer
  • AI-Engineering
  • AI-Engineering-Specialist
  • AI-ML-Engineer
  • AI-Machine-Learning-Engineer
  • Agent-Engineering
  • Artificial-Intelligence-Engineer
  • Autonomous-AI
  • Data Science
  • Financial-Services
  • LLM-Engineering
  • MLOps
  • Machine-Learning-Engineering

Assessed from original listing evidence

The role

Job description

A leading company in Mexico specializing in accounting software is looking for a highly skilled AI Engineer to join the team.

REQUIREMENTS:

  • 5 years of experience in artificial intelligence projects and 2 years in the implementation of autonomous agents or co-pilots.
  • Fluent technical English.
  • Experience working with business data in domains such as accounting, finance, payroll, billing, or ERP.
  • Experience working with vector stores (Chroma, Weaviate, Pinecone) and RAG architectures.

KNOWLEDGE AND SKILLS:

  • Handling frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar.
  • Practical knowledge of MCP and A2A protocols, use of tools, memory management, and conversation status.
  • Solid command of Python and experience with FastAPI, asyncio, Pydantic, and asynchronous architectures.
  • Knowledge of MLOps: CI/CD, Docker, Kubernetes, agent monitoring, and automated retraining.
  • Practical knowledge of other languages such as Golang, Java, or C# (.NET), especially in building high-performance components (Nice to Have).

RESPONSABILITIES:

  • Define, design, and supervise the technical architecture of solutions based on intelligent agents and LLMs, integrating tools such as LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent frameworks.
  • Implement MCP (Model Context Protocol) and A2A (Agent-to-Agent) architectures to enable multi-agent coordination and autonomous flows within business environments.
  • Work with the MLOps team and execution environments that enable continuous agent updating and deployment, including memory management, context, and long-term planning.
  • Collaborate closely with product, UX, data, and backend teams to map business needs to intelligent agent architectures.

Originally posted on Himalayas

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