Top Artificial Intelligence Jobs in Mexico

Design, build, and operate production AI systems, enhance backend services, improve reliability, and collaborate on technical projects within the AI-native engineering team.

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

As a Staff Software Engineer at Juniper Square, you'll lead architectural decisions and develop AI-powered systems, mentoring engineers and ensuring high-quality technical standards while collaborating with cross-functional teams.

Evaluate AI-generated Computer Science content for factual accuracy and reasoning; craft and answer domain-specific questions; rank and provide expert feedback on model responses; develop prompts and support AI training initiatives to improve model performance.

The role involves designing, developing, and deploying AI/ML solutions focusing on Retrieval-Augmented Generation. The engineer will optimize retrieval performance, build data pipelines, and collaborate within teams while staying updated on AI advancements.

Create cinematic short-form storytelling and AI-driven visual content using generative AI tools. Develop AI-powered production workflows, execute and iterate on creative projects, collaborate remotely, and deliver portfolio-quality AI-generated videos and experimental storytelling across social and digital platforms.

The Digital Software Engineer VP leads a professional team in designing and implementing AI/ML solutions for digital experiences, managing systems for real-time customer interactions, and ensuring system performance across various platforms.

Design, build, and deploy generative AI solutions and agentic workflows using LLMs. Implement RAG architectures with vector databases, integrate AI services with enterprise systems, deploy AI workloads on AWS, and ensure monitoring, governance, and security for production AI applications.

Lead backlog ownership for complex, multi-team AI-centered engagements. Translate product strategy into epics and stories, drive ambiguity resolution, facilitate refinement and Agile ceremonies, mentor other POs, partner with UX, and champion AI-forward backlog and documentation practices to ensure delivery quality and clear client communication.

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.

Lead AI capability strategy and implementation for Salesforce (SFDC). Translate business needs into AI-enabled requirements, design and deliver solutions, run POCs, establish governance, assess vendors, ensure secure scalable integrations, and align cross-functional stakeholders to drive AI-enabled sales productivity and user experience.

As a Customer Technology Advisor at Kyndryl, you'll leverage your domain expertise and customer relations skills to deliver tailored technology solutions, drive sales, and exceed customer expectations through compelling proposals and collaboration with technical teams.

The AI Strategy Consultant will drive marketing strategy using AI, work with teams to implement solutions, and enhance customer outcomes.

The role involves rapid prototyping and architecting production LLM pipelines for AI in marketing workflows. Responsibilities include developing proofs of concept, making AI architecture decisions, building production data agents, and understanding user workflows for seamless AI experiences.

Lead design and build of AI agents and integrations across pro-code and no-code platforms. Define automation patterns, integrate AI platforms with business tools via APIs, write Python for complex integrations and data transforms, evaluate agent performance, and guide architecture and tooling decisions while collaborating with VP of AI.

The Senior Advanced Data Engineer designs, develops, and maintains data solutions, implements data models, manages workflows, ensures data quality, and collaborates with teams for business insights.

As a Principal Software Architect, you'll lead platform integrations, architect scalable cloud-native applications, and leverage AI/ML for enhanced security. You'll work collaboratively across teams and mentor engineers while ensuring system optimization and operational excellence.

The ML Engineer will design, build, and operationalize AI systems for unstructured data, developing ML pipelines and collaborating with Data Scientists and Engineers to deliver scalable AI solutions.

The Applied AI Engineer will develop and deploy AI automation solutions, integrate LLMs, and collaborate with clients to enhance workflows and systems.

The Data Quality Engineer ensures the quality and integrity of data in studies, developing measurement systems, automation, and conducting analysis to uphold standards across projects.

The Sr. AI Engineer will design and implement scalable machine learning models, optimize ML operations, and mentor team members while collaborating across departments to enhance AI-driven features.

Lead the definition and governance of enterprise AI architecture; design and oversee LLM-powered systems, RAG pipelines, agentic frameworks, and inference infrastructure; advise executives on AI strategy and risk; create reusable AI reference architectures and CoE artifacts; mentor engineers and integrate AI into DevOps/QA practices while ensuring regulatory and security compliance.

Design and build end-to-end web applications using .NET (Framework/Core) back-ends and modern front-end frameworks (React, Angular, Vue). Implement cloud-native solutions (Azure/AWS), optimize MS SQL databases, apply SOLID/design patterns, create unit/integration tests, lead Agile teams, set up CI/CD, use AI coding assistants, deploy AI features to production, and mentor peers in a collaborative multicultural environment.

The role involves onboarding new clients, configuring AI assistants, managing onboarding timelines, and providing client support to ensure successful implementations.