AI Engineer

POSITION SUMMARY

We are seeking a highly motivated and technically skilled AI Engineer (Contract) to join our team.

This is a fully remote position based in Mexico, working within a distributed LATAM-based technical team. The AI Engineer serves as a hands-on, execution-focused engineer responsible for building and operating generative AI systems, supporting the evolution of internal AI assistant capabilities, and contributing to the engineering infrastructure powering AI initiatives across multiple workstreams.

Positioned as a critical delivery resource within the AI Strategy and Innovation function, this individual works closely with the Lead AI Engineer & Architect to implement, maintain, and continuously improve AI agents, LLMOps frameworks, and classical ML systems in production. This role also supports broader AI enablement efforts, helping business stakeholders learn to build AI assistants and agents using Microsoft Copilot Studio, bridging technical execution with organizational adoption.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Build and maintain AI agents in Azure AI Foundry
  Develop new agents from defined specifications and enhance existing agents in production, ensuring quality, reliability, and alignment with business requirements.
• Support internal AI assistant capabilities
  Maintain and improve internal AI assistants, including agent integration, prompt iteration, and performance tuning.
• Contribute to platform integrations
  Support integrations between AI assistants and adjacent platforms such as Copilot Studio, ensuring seamless interoperability across the AI ecosystem.
• Implement the LLMOps framework
  Contribute to evaluation pipelines, prompt versioning, observability tooling, and cost monitoring for generative AI systems.
• Operate classical machine learning models in production
  Support scheduled retraining, performance monitoring, and troubleshooting for classification, regression, and time series models.
• Build monitoring and observability tooling
  Develop dashboards, alerts, and operational runbooks to ensure ML models and AI agents remain healthy and performant in production.
• Collaborate with QA
  Work with QA to ensure models and agents continue to meet established quality standards. Support recurring evaluation cycles as needed.
• Write clear technical documentation
  Produce code documentation, README files, operational runbooks, and feature documentation for production AI systems.
• Provide first-level technical support
  Troubleshoot non-critical issues raised by stakeholders interacting with AI systems and escalate where appropriate.
• Support AI enablement efforts
  Contribute to AI enablement by supporting business stakeholders as they learn to build AI assistants and agents using Microsoft Copilot Studio. Participate in office hours, deep-dive sessions, and hands-on learning.

QUALIFICATIONS

• Minimum 4 years of experience as an AI Engineer, ML Engineer, or similar hands-on engineering role
• Experience building or operating LLM-based systems in production, including AI agents, RAG pipelines, prompt engineering, and vector stores
• Familiarity with Azure AI Foundry, LangChain, Semantic Kernel, or similar frameworks preferred
• Strong Python skills with production-grade backend development experience
• Experience with at least one major cloud AI platform (Azure strongly preferred; AWS/GCP acceptable)
• Working knowledge of classical ML libraries including scikit-learn, XGBoost, pandas, numpy
• Understanding of MLOps and LLMOps practices including model versioning, CI/CD, monitoring, evaluation frameworks, experiment tracking (MLflow or similar)
• Experience deploying and operating AI/ML systems in production
• Strong English communication skills
• Comfortable working independently while collaborating with distributed teams
• Ability to support non-technical stakeholders in enablement/training scenarios

PREFERRED

• Hands-on Microsoft Copilot Studio or Power Platform experience
• Experience supporting AI training or enablement for non-technical teams
• Familiarity with workflow automation / RPA concepts
• Experience in agile delivery environments