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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