AI DevOps Engineer (nearshore)

Title: AI DevOps Engineer
Location : Mexico (remote)
Target Start Date : ASAP
Type: Contract
Pay Rate : $500.00-$525.00/day (USD)
Overview
Our client, a global leader in the design and manufacture of consumer and safety products, is seeking an AI DevOps Engineer to design, develop, and deploy AI-powered solutions that improve business processes, decision-making, and operational efficiency.
This role focuses on agentic AI, intelligent automation, and AI-enabled enterprise integrations and develop production-ready solutions, and integrate AI capabilities with enterprise applications, data, and workflows.
The ideal candidate is comfortable working across a rapidly evolving AI ecosystem and evaluating the right tools and platforms for each use case, including AWS Bedrock, Microsoft Copilot, Copilot Studio, GitHub Copilot, Claude Code, LLM APIs, AI agents, and emerging AI integration technologies such as Model Context Protocol (MCP).
Key Responsibilities
Design, develop, and deploy AI-powered applications, agents, and intelligent automation solutions using commercial and open-source AI/LLM platforms.
Develop agentic AI workflows capable of reasoning, orchestrating tasks, interacting with systems, and supporting human decision-making.
Evaluate and leverage AI platforms and tools including AWS Bedrock, Microsoft Copilot, Copilot Studio, GitHub Copilot, Claude Code, and other emerging AI technologies.
Integrate AI capabilities with enterprise applications, APIs, databases, data platforms, and business workflows.
Develop AI integrations using technologies such as MCP (Model Context Protocol), APIs, connectors, tool calling, function calling, and other emerging AI integration patterns.
Partner with business and functional leaders to understand processes, identify high-value AI use cases, and translate business needs into technical solutions.
Build AI solutions that support automation, knowledge retrieval, reporting, analytics, decision support, exception management, root-cause analysis, and process optimization.
Develop and integrate AI agents with enterprise platforms such as ERP, MES, PLM, supply chain, finance, collaboration, and data systems.
Apply AI and LLM technologies to enterprise data to generate insights, automate analysis, and improve decision-making.
Design prompts, agent instructions, tools, workflows, and integrations that improve the reliability and effectiveness of AI solutions.
Evaluate AI models and platforms based on capability, cost, performance, security, scalability, and business value.
Monitor, test, measure, and continuously improve AI solutions for accuracy, reliability, performance, and measurable business impact.
Collaborate with data, software, automation, cybersecurity, and enterprise technology teams to deploy AI solutions into production environments.
Contribute to enterprise standards for AI governance, security, privacy, responsible AI, and data stewardship.
Required Qualifications
Hands-on experience developing agentic AI, generative AI, LLM, and/or intelligent automation solutions.
Strong understanding of AI agents, LLMs, prompt engineering, tool/function calling, RAG, and AI workflow orchestration.
Experience working with one or more enterprise AI/LLM platforms such as AWS Bedrock, Microsoft Copilot/Copilot Studio, Azure AI, OpenAI, Anthropic/Claude, or similar technologies.
Experience integrating AI solutions with enterprise systems, APIs, databases, data platforms, and business applications.
Familiarity with emerging AI integration technologies such as MCP, AI connectors, APIs, tool calling, or agent frameworks.
Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, or similar AI coding/development platforms.
Ability to analyze complex business processes and translate business challenges into practical AI use cases and technical solutions.
Experience developing AI solutions for data analysis, reporting, knowledge retrieval, automation, or decision support.
Strong programming/software development experience with languages such as Python, JavaScript/TypeScript, or similar.
Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
Preferred Qualifications
Experience in manufacturing, supply chain, industrial, consumer products, or other complex enterprise environments.
Experience with ERP, MES, PLM, supply chain, quality, production, or other enterprise business systems.
Experience with AWS, Azure, or other cloud platforms.
Experience with AI/ML frameworks, vector databases, RAG architectures, agent frameworks, or orchestration platforms.
Experience implementing MCP servers/clients or other AI-to-system integration patterns.
Background in process engineering, continuous improvement, digital transformation, software engineering, data engineering, or intelligent automation.
Experience establishing AI governance, security, compliance, evaluation, or responsible AI practices.
Experience working with multiple LLM providers and selecting models based on specific business and technical requirements.
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Work arrangement
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