Top Artificial Intelligence Jobs in Mexico

Design, build, and scale end-to-end AI agent-driven workflows that automate marketing and business processes. Translate requirements into reliable, monitored agent systems, define guardrails and validation, optimize prompts and tool usage, and integrate APIs, databases, and reporting tools to improve efficiency with minimal human intervention.

Support the development and deployment of RPA solutions, collaborating with teams to design, test, and implement automation processes using tools like UiPath.

Lead enterprise customer workshops to assess AI readiness and implement AI governance frameworks. Translate Microsoft security and compliance capabilities into actionable controls, advise secure adoption of generative AI, design data protection/DLP and identity controls, recommend monitoring and incident-response for AI misuse, and present findings to IT executive stakeholders.

Architect and deliver AI-native multi-agent systems for sales: design agentic architectures, integrate with CRM and data platforms, own product backlog and roadmap, define success metrics, ensure production reliability, and lead releases and stakeholder alignment.

Build, configure, and optimize AI-powered agents, workflows, and conversational experiences for HR and workplace systems. Implement end-to-end use cases, integrate enterprise systems, ensure privacy/security compliance, monitor quality metrics, and create reusable templates and documentation while collaborating with global People & Places, IT, and Security teams.

Freelance senior illustrator creates high-quality digital illustrations across varied styles, producing characters, environments, and concept art. Documents prompts and style decisions, collaborates with AI researchers, incorporates feedback, and delivers production-ready artwork on schedule.

Design and implement AI-powered business workflows using Microsoft Copilot Studio and Power Platform (Power Apps, Power Automate, AI Builder). Build automations, conversational experiences, and integrations with SharePoint and REST APIs. Collaborate with solution architects and technical leads to support implementation, integration, testing, and deployment across enterprise processes.

Support software development, data analysis, and AI/ML initiatives across the SDLC. Build scalable applications, contribute to AI/ML use cases, automate processes, generate data insights, deliver clean code, and collaborate with cross-functional teams under mentorship.

The Machine Learning Analyst collaborates with AI/ML teams to identify data requirements, implements data ingestion pipelines, and ensures data quality while supporting data scientists in model development.

Lead multiple concurrent AI and technology projects from initiation to delivery. Develop project plans, coordinate cross-functional teams, manage client relationships, mitigate risks, track performance metrics, and ensure alignment with business objectives across Agile, Waterfall, or hybrid environments.

Participate in a 14-day remote notification-sorting pilot using a qualifying Google Pixel device. Interact naturally with apps that generate notifications, complete daily sorting tasks and short feedback forms, report issues, and follow project instructions. Must provide clear, consistent daily participation and documentation.

Join the AI Special Forces team to provide high-quality customer support, troubleshoot technical issues, and collaborate with teams to enhance client satisfaction with AI technologies.

As an Onboarding Executive, you will facilitate the onboarding process for new clients, ensuring smooth implementation and effective communication while building AI assistants tailored to client needs.

You will onboard new accounts, support clients with AI tools, and assist in enhancing their business through technology.

Assist clients with AI-related technical issues, providing support, troubleshooting, and collaborating with internal teams to ensure customer satisfaction.

The IA Operations Executive aids in onboarding new client accounts, builds AI assistants, aligns client requirements, and ensures successful implementation processes.

The AI Developer will design, train, optimize, and deploy LLM models, develop backend services and maintain models in offline environments, focusing on ML engineering and optimizing workflows.

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

As an AI Software Engineer, you will develop Generative AI solutions, manage full-cycle development, implement MLOps pipelines, and ensure compliance with AI standards.

The role involves designing and optimizing model-zoo infrastructure for AI accelerators, developing demo applications, and enhancing existing CNN and LLM models. It requires collaboration on workflows and performance benchmarking for computer vision and generative AI applications.

Design and implement AI-driven applications using Verint technology, working with cross-functional teams to enhance customer experience and operational efficiency.

Design, build, and deploy agentic AI applications and multi-agent systems using LLMs, RAG, tool-calling, memory and orchestration frameworks. Integrate agents with enterprise platforms, evaluate foundation models, implement observability and guardrails, and optimize production performance across latency, accuracy, reliability, and cost.

As an AI/ML Engineer, design and implement AI solutions, collaborate with teams, build ML pipelines, and ensure quality and compliance in healthcare applications.

Part-time MBA/graduate internship to build scalable BI and AI-enabled analytics frameworks. Tasks include cleaning and prototyping data workflows, upgrading dashboards, embedding natural-language queries, automating executive summaries, and documenting data flow improvements for GTM decision-making.

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.