Top Artificial Intelligence Jobs in Mexico

Leads HR strategy and organizational effectiveness across LATAM, advising executives, driving AI transformation, talent initiatives, employee experience, compliance, and regional HR operations. Partners with global People teams and local stakeholders on workforce planning, succession, retention, compensation, employee relations, labor law, entity setup, and international growth. The role requires strategic influence, executive coaching, analytical decision-making, and hands-on execution across Mexico, Brazil, Colombia, Argentina, and Chile.

Own daily operations and quality assurance for an internal AI-powered growth platform. Test releases, rule changes, edge cases, and regressions; document and verify bug fixes; monitor platform and agent activity; manage approval queues; evaluate agent output; escalate risks; and maintain test plans, QA checklists, runbooks, and release notes.

Support clients and senior consultants with health and life insurance benefits analysis, plan competitiveness assessments, cost-containment opportunities, client strategy alignment, escalated cases, and portfolio maintenance. Build client relationships, contribute to strategic discussions, and develop recommendations based on market data and industry trends while participating in Marsh’s training and development program.

Drive end-to-end B2B partner marketing campaigns for complex technology and business transformation propositions. Develop positioning, messaging, content, and integrated campaign strategies; coordinate global teams, creative resources, and technology partners including Microsoft, AWS, and Google. Manage partner investments, measure campaign performance, optimize results, and apply AI to improve marketing workflows, insights, reporting, and operational efficiency.

Designs and maintains scalable AWS cloud infrastructure, develops CI/CD pipelines, automates infrastructure with Terraform or CloudFormation, monitors and optimizes application performance, troubleshoots infrastructure issues, collaborates with development teams, and ensures cloud security compliance.

Build scalable software, data pipelines, analytical applications, and AI solutions for agricultural R&D data. Develop and deploy machine learning models, cloud-native applications, APIs, and containerized systems in AWS environments. Partner with scientists and analytics teams to translate research needs into reliable, explainable production tools. Apply agentic AI and AI-assisted development responsibly while ensuring testing, governance, security, compliance, and scientific validity.

Builds scalable software, data pipelines, analytical applications, and AI solutions for agricultural R&D. The role integrates scientific datasets, machine learning models, agentic AI, and domain-specific workflows while deploying reliable cloud-native systems. Responsibilities include production ML deployment, containerization, API development, collaboration with scientists, AI tool evaluation, and ensuring explainability, governance, security, and compliance.

Produces commercial AI-generated images and videos using generative models, prompt engineering, model training, and custom creative workflows. Collaborates with designers, editors, strategists, and clients to deliver brand-aligned assets. Improves internal AI tools, tests emerging models, develops reusable processes, performs quality assurance, documents workflows, and coaches creative teams on AI techniques and tool selection.

Build a production-grade AWS service for Kyveria, automating customer interaction quality evaluation with Claude across Salesforce, contact center, and chat channels. Responsibilities include migrating workflows, integrating external data sources, designing versioned AI evaluation pipelines, measuring model consistency against human reviewers, improving prompts and rubrics, and collaborating with CX teams and BPOs to deliver actionable agent feedback.

Mercor is offering $5 million in grants for research on AI capabilities, including real-world evaluations, interactive environments, long-horizon tasks, agentic systems, reasoning, post-training, and evaluation methodology. Academic groups, independent researchers, and nonprofits may apply with a focused proposal. Applicants should describe their team, background, research accomplishments, project, expected outputs, impact, timeline, and resource needs. Funded projects are expected to produce public research, datasets, methodologies, or tools.

Build and maintain AI agents for risk and collections using Claude. Develop reliable, parallel, cost-efficient processing with evidence-backed outputs; implement caching, batching, model routing, retries, evaluations, prompt versioning, and secure OIDC/Okta access controls. Collaborate with Risk Data Science and external agencies to validate findings and support auditable case workflows.

Conduct offensive, AI-driven red-team assessments by validating automated attacker decisions, resolving authentication and CAPTCHA challenges, guiding reconnaissance, classifying attack data, and providing feedback to improve security models. The role requires maintaining context across multiple client engagements, making safety-critical judgments, and documenting technical decisions. Candidates need at least one year of relevant experience through work, internships, classes, or projects, plus authorization to work in Mexico without sponsorship.

Build and maintain production-grade LLM applications, agentic AI systems, and MCP servers. Design intent classification, evaluation, routing, and multi-API orchestration workflows; integrate Anthropic and OpenAI models; optimize prompts, cost, latency, and performance; and write SQL for monitoring and evaluation. Work within a partially documented Python codebase, contribute to architecture, and collaborate with engineering and AI teams to deliver reliable conversational AI solutions.

Design, build, and optimize scalable ETL/ELT pipelines and data models using dbt, Snowflake, Informatica, and Airflow. Integrate data from multiple systems, ensure data quality and governance, support analytics and machine learning use cases, and troubleshoot pipeline performance issues. Collaborate with analysts, product managers, and business teams to deliver reliable data solutions while improving engineering processes, documentation, and platform scalability.

Leads cross-functional teams building scalable AI-driven applications using Python, Java, TypeScript, and GCP. Designs databases, integrates Google ADK services, oversees architecture and code quality, mentors engineers, and collaborates with product stakeholders on technical roadmaps. The role also promotes AI-native development practices and continuous innovation.

Lead Kraken Pro’s social media strategy across X, Telegram, and other platforms. Create platform-native content, react quickly to crypto and trading trends, manage the content calendar, engage the community, translate product updates into compelling narratives, track performance, and optimize through experimentation. Partner with Legal and Communications to ensure accurate, compliant messaging across regions.

Own and optimize PayJoy’s AI-powered telesales channel, including voice bot operations, agent deployment, vendor integration, customer journey improvements, and channel experimentation. The role establishes quality and compliance standards, analyzes customer conversations, tracks KPIs, and collaborates with Marketing, Product, Product Marketing, and Analytics to improve conversion, retention, and engagement.

Oversee platform security and networking from design through remediation. Responsibilities include threat modeling, security policy development, secrets and KMS design, token vault management, penetration-testing oversight, vulnerability remediation, Google Cloud security, API and OAuth security, and Kubernetes/container hardening. The role also supports compliance with SOC 2, ISO 27001, and GDPR for SaaS environments.

Designs, builds, and operates enterprise conversational agents, custom copilots, and agentic workflows. Integrates AI solutions with Snowflake, SharePoint, and Azure; manages CI/CD deployments and resilient cloud infrastructure; and develops Splunk-based observability, logging, and governance. Provides technical leadership to global teams and uses AI-assisted development tools to improve engineering productivity.

Create short films and videos using AI photo and video generation tools. Edit AI-generated content, develop concepts with marketing teams, maintain brand alignment, experiment with creative formats, and deliver engaging content for Tether and affiliated brands. The role requires video production and editing expertise, strong storytelling and visual composition skills, familiarity with digital marketing and social media, and the ability to manage multiple projects independently under tight deadlines.

Build and ship features for an AI-powered risk intelligence platform using spec-driven, AI-assisted development. Translate requirements into specifications, direct AI coding agents, review and test generated code, develop backend services and APIs, define acceptance criteria, maintain development standards, and improve CI/CD workflows. The role requires end-to-end feature ownership, strong testing practices, cloud deployment experience, and excellent English communication with a US-based client team.

Build and maintain open source AI integrations, frameworks, SDKs, notebooks, and example applications integrating AI workflows with Backblaze B2 Cloud Storage. Develop production-quality code using multiple open source languages and AI coding agents, contribute to public repositories, and ensure strong testing, documentation, security, reproducibility, and developer usability. Collaborate with Product and QA to support real-world AI workflows.

Lead large Microsoft Dynamics 365 (CRM/CE) implementations as a Senior Manager: engage senior clients, design functional solutions, oversee delivery lifecycle, coach teams, refine processes, and ensure operational excellence and adherence to firm standards.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Senior Data Analyst responsible for analyzing large datasets, designing scalable databases, applying ETL and artificial intelligence techniques, automating workflows, improving processes, generating reports, and coordinating technical projects from planning through closure. The role requires SQL Server, Azure Data Tools, Python, database design, data management, automation, and strong leadership and project coordination skills.