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Metova

Metova

via Workable

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AI Engineer

Anywhere
Full-time
Posted 12/8/2025
Direct Apply
Key Skills:
Python
FastAPI
asyncio
Pydantic
LangChain
LlamaIndex
AutoGen
CrewAI
Semantic Kernel
MLOps
Docker
Kubernetes
Golang
Java
C#

Compensation

Salary Range

$120K - 160K a year

Responsibilities

Design and supervise AI agent architectures integrating LLM frameworks and coordinate multi-agent autonomous flows in business environments.

Requirements

5+ years AI project experience including 2+ years with autonomous agents, fluent English, business domain experience, and knowledge of vector stores and MLOps.

Full 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.

This job posting was last updated on 12/9/2025

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