Top Artificial Intelligence Jobs in Mexico City

Leads DXC’s AI-first sales transformation by designing autonomous agents, generative AI solutions, and automation to replace inefficient sales processes. Prototypes and tests MVPs with sellers, evaluates emerging AI technologies, develops the 12–24 month AI-native sales roadmap, and drives organizational adoption. The role partners with sales leadership to identify high-impact opportunities and communicates a compelling vision for transformational revenue improvements.

Design and own AI platform foundations for an enterprise CPQ modernization. Responsibilities include AI data modeling, data quality pipelines, LLM and MCP integrations, vector retrieval, AI constitutions, guardrails, workflow agents, developer tooling, evaluation systems, and architecture prototyping. The role also develops documentation, trains team members in AI literacy and verification, reduces key-person risk, and supports adoption of an Intent–Generate–Verify–Decide–Document workflow.

Own the architecture, deployment, reliability, and cost optimization of production AI/ML infrastructure on GCP. Build model serving systems, reproducible ML pipelines, GitOps workflows, and multi-tenant Kubernetes platforms. Manage LLM and agentic workloads, Terraform infrastructure, observability, SLOs, drift monitoring, accelerator capacity, and inference costs. Define operational standards, improve automation, and guide platform evolution for scalable enterprise-grade ML systems.

Lead the architecture and delivery of complex, production-grade digital products while remaining hands-on in React, TypeScript, AWS, APIs, backend services, and distributed systems. Partner directly with clients and senior stakeholders, guide technical decisions, lead projects from discovery through production, mentor engineers, and establish engineering standards. Incorporate AI-assisted and agentic coding tools into development workflows, with opportunities to build AI-powered applications and lead cloud modernization initiatives.

Architect and deliver production-grade cross-platform mobile applications using Flutter and/or React Native. Lead architecture, development, testing, performance optimization, CI/CD, and App Store and Google Play deployment. Integrate APIs, cloud services, authentication, SDKs, and AI/LLM capabilities. Collaborate with clients and product teams, make pragmatic technical decisions, mentor engineers, and establish mobile engineering standards while using AI-assisted and agentic development tools.

The Senior Product Manager for AI will lead the AI transformation at Aplazo by owning the AI roadmap, delivering AI-powered features, and developing internal tools, all while collaborating with cross-functional teams.

Own Aleph’s shared AI foundation, including model selection and routing, proxy infrastructure, context management, tool design, and evaluation systems. Ship production agentic features using prompt engineering, caching, parallel tool calls, and subagents. Build observability for agent performance, collaborate with customers and finance experts to define quality standards, and drive adoption of reliable AI systems across product teams.

Industry Expert who reviews advanced AI and systems engineering projects, leads technical defenses and mock architecture review boards, hosts occasional design sessions, and sets technical standards for instructors. The role requires senior-level production engineering experience, strong architectural judgment, the ability to critique systems live, and expertise in AI/ML engineering, AI systems, or forward-deployed engineering. This is a fully remote commitment of 4–10 hours monthly with negotiable hourly compensation.

Designs, develops, integrates, and deploys intelligent solutions using machine learning, deep learning, generative AI, and LLMs. Builds production-ready AI applications, RAG pipelines, and NLP systems; manages model evaluation, optimization, monitoring, versioning, and deployment. Collaborates with engineering, product, and data teams in a distributed environment while emphasizing scalability, maintainability, testing, observability, responsible AI, and cost efficiency.

Design, build, deploy, and troubleshoot production-grade AI applications, integrations, pipelines, and agentic workflows for customers. Lead technical discovery, workshops, architecture discussions, prototyping, and go-live support. Translate customer needs into reliable systems and product feedback, establish reusable engineering patterns, collaborate across Product, Sales Engineering, Customer Success, and Engineering, and mentor customer-facing engineers. Travel to customer sites as needed.

Design and optimize Databricks Lakehouse architectures and scalable ETL/ELT pipelines across AWS, Azure, and GCP. Build Spark and Delta Lake workflows for structured and unstructured data, tune performance and cloud costs, and integrate MLflow for AI model operationalization. Implement CI/CD and infrastructure-as-code deployments, enforce governance and security through Unity Catalog, and collaborate with client leaders to deliver production-ready data and AI solutions.

The AI & Software Engineering Senior Manager directs a team in developing innovative digital marketing solutions, manages product roadmaps, and drives AI-powered projects for high-impact results in the media and advertising sector.

Design, develop, and deploy enterprise AI applications using .NET, C#, Python, Azure, LLMs, Generative AI, and Agentic AI. Build intelligent agents, multi-agent workflows, and RAG solutions with vector databases. Integrate AI services with enterprise systems, APIs, and data platforms while ensuring security, governance, scalability, and performance. Mentor engineers, conduct code reviews, collaborate with stakeholders, and establish AI engineering best practices.

This role involves leading strategic planning, product innovation, and cross-functional collaboration to enhance pharmacy analytics and drive growth initiatives for CVS Health.

Develop and maintain MCP tools and the MCP Toolbox for Databases; expand test coverage for agentic coding assistants; refactor and maintain test frameworks; convert technical posts into production-ready sample code and documentation; build real-world data applications (QueryData) to support product R&D and collaborate with cross-functional teams to accelerate agentic AI adoption.

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

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

Build and maintain end-to-end data pipelines, models, data marts, and semantic layers supporting agency, client, BI, product, and AI consumers. Integrate fragmented marketing and customer data across advertising platforms, e-commerce, analytics, and CRM systems. Manage dbt projects, multi-tenant Snowflake infrastructure, data quality, performance, and client-specific modeling. Use AI coding agents, cloud infrastructure, CI/CD, and automated testing while collaborating across product, engineering, analytics, and client teams.

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

Work on customer-facing AI projects building AI-powered applications, intelligent agents, and automation workflows. Experiment with LLMs and cloud-native technologies, contribute reusable components to the platform, support design/testing/deployment, participate in code reviews, document solutions, and research emerging AI tools and best practices.

Designs, builds, and optimizes enterprise-grade AI agents and scalable AI architectures. Advises enterprise leaders on AI strategy, leads agent development from scoping through production optimization, maps business challenges into technical workflows, collaborates with engineering and product teams, monitors live systems, troubleshoots issues, and identifies product improvements. Requires strong AI/ML, agent architecture, enterprise integration, consulting, and executive advisory expertise.

Design, build, and operate scalable cloud backend services that power LLM-driven features (inference, RAG, agents). Own end-to-end delivery including IaC (Terraform), CI/CD, monitoring, and incident response; collaborate across product, UX, and platform teams.

Design, build, and operate scalable, highly available backend cloud services that power LLM-driven features (inference, RAG, agents). Own end-to-end delivery including IaC, CI/CD, monitoring, and incident response; collaborate across product, UX, and platform teams to deploy multi-tenant SaaS solutions on Azure and Kubernetes.

The Social Media & Content Operations Assistant executes content management and lead handling tasks, utilizing structured AI workflows and tools, while maintaining organization and consistency within the operations.

Design, build, and deploy end-to-end LLM-based AI applications (RAG, fine-tuning, embeddings). Work with founders and clients, iterate rapidly, and own production delivery including cloud deployment and ML pipelines. Occasionally contribute to frontend, dev tooling, or data pipelines.