Top Artificial Intelligence Jobs in Mexico

Early-career operations role executing Salesforce system enhancements, resolving process issues, building reports/dashboards, implementing Flows and minor Apex updates, and applying AI tools to improve post-sales CX workflows.

The Tech & AI Content Course Creator will design AI curricula, create hands-on projects, prototype workflows, and adapt tech trends for the Hong Kong and Singapore markets, while collaborating globally and iterating based on feedback.

As a Lead Software Engineer at PMG, you will design, develop, and deploy scalable AI-driven solutions, mentor other engineers, and enhance the Alli platform for digital marketing. Responsibilities include coding, code reviews, and integration with cross-functional teams.

Manage and optimize the GTM technology stack (Salesforce, Marketo, Outreach, Gainsight), lead integrations, automate processes, support and train GTM teams, build reports/dashboards, manage vendors, ensure data governance and run GTM systems projects from design through deployment.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

The role involves evaluating AI-generated content, generating original content, and providing structured feedback informed by local cultural insights while working flexibly as an independent contractor.

The role involves developing features for an AI platform, designing architectures, building backend services in Python, and frontend components with React, ensuring performance and scalability while collaborating in a startup environment.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Lead design and implementation of a scalable, secure multi-tenant SaaS using .NET and Angular. Own full-stack delivery from domain modeling through frontend, automated testing, CI/CD, and production support while mentoring engineers and leveraging AI-assisted development to accelerate quality delivery.

Lead architecture and development of AI-first backend systems and orchestration for Audit Suite. Drive AI integration (LLMs, retrieval, vector stores), ensure scalability, reliability, observability, and compliance. Mentor engineers, lead cross-functional initiatives, shape roadmap and platform integration, and implement high-throughput, low-latency AI workflows across heterogeneous stacks.

The role involves creating narrative-driven content using AI video tools, managing production workflows, and ensuring visual storytelling consistency. The editor will work independently on concept creation, editing, and post-production, focusing on both artistic and technical elements of AI-generated video.

Develop server-side APIs for user authentication and data management, utilizing AI-assisted tools while ensuring code quality and addressing customer issues at scale.

As a Senior Software Engineer specializing in AI, you will develop server-side APIs, leverage AI development tools, and support customer issue resolution while maintaining high coding standards across various backend languages and tools.

The Software Engineer, AI designs and builds server-side APIs, collaborates with teams, and ensures high standards in code and tools, focusing on AI-assisted development.

The Freelance AI Artist will produce high-quality images and videos using AI technologies, collaborating with marketing to align with brand identity and experimenting with new workflows.

The AI Specialist responds to customer inquiries, troubleshoots tech issues related to AI, and collaborates with teams for client satisfaction.

As a Marketing Data Scientist at Vonage, you will bridge data and AI, ensuring data readiness for AI applications in marketing. Responsibilities include data structuring, collaboration with engineering, and automating data validation processes.

Lead client-specific QA programs for generative AI projects: set sampling and acceptance thresholds, run root-cause analyses and CAPA, design training and certification, maintain dashboards and KPIs, manage escalations, standardize SOPs, pilot automations, coach annotators, and ensure secure data handling across distributed teams.

Manage quality, workforce, and training programs for multilingual generative AI data projects. Oversee QA, capacity planning, training, dashboards, compliance, process improvement, stakeholder reviews, team coaching, and risk/change control to meet client SLAs and delivery targets.