Top Artificial Intelligence Jobs in Mexico City

Join a small cross-functional team to design, build, and operate an LLM-powered agent platform: orchestration, tool integrations, APIs, knowledge/memory infrastructure, trust & safety, evaluation/testing, and partner with Operations to translate workflows into automation. Mentor other engineers and deliver production-ready systems.

As a Sr. Lead AI Engineer, you will develop the agent harness for supplier agents, focusing on platform design and cloud infrastructure deployment while collaborating with product and engineering teams.

As a Lead AI Engineer, you will build an AI harness for supplier agents, manage context, design sub-agent patterns, and debug production behaviors, collaborating with a senior engineer on architecture.

Own end-to-end operational health for payment partners in Mexico, monitoring KPIs, troubleshooting integrations, analyzing large datasets, and driving improvements in payment flows, routing, and partner performance. Lead RCAs, build dashboards, present executive BEAT reports, and support product and growth teams with data-driven insights and automation/AI initiatives.

Deploy, configure, tune, and support CrowdStrike Falcon AI/ML detection and response capabilities. Optimize ML models, build automation playbooks, integrate AI into customer workflows, develop Falcon API scripts, support incident response and threat hunting, and deliver AI training and customer-facing collateral. Travel up to 25%.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, including LLM inference infrastructure, RAG, AI agents, and evaluation/observability. Design and run experiments (A/B tests), optimize systems for production performance and reliability, and iterate rapidly with product and design partners.

Design, develop, test, and deploy AI-based solutions and automations to improve business workflows. Partner with stakeholders to define requirements, validate models (including LLMs and NLP), and expand Aladdin Compliance and Accounting platform capabilities.

Drive partner and customer adoption of Microsoft Fabric and Data & AI solutions. Build and enable partner network, generate pipeline, run enablement events, collaborate with internal sales and technical teams, support customer conversations, monitor KPIs, and promote Azure-based data and AI offerings.

The Technical Advisor manages post-sales customer relationships, providing cybersecurity expertise and supporting adoption of the TrendAI platform to strengthen security posture and drive value realization.

Own strategy for a reusable lending platform and identity data platform. Define identity and authentication flows, data schemas, and API design. Align engineering, fraud, compliance, and partner banks. Drive KPIs, AI-enabled identity decisioning, and platform adoption. Start as a strategist and build a team to scale lending products.

Lead IT operations across six Latin American countries, owning strategy, cloud and infrastructure, cybersecurity governance, service delivery, budgets, vendor management, and regional IT team development.

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

Support Mexico controllership by monitoring regulatory changes, maintaining internal controls, preparing local GAAP financial statement disclosures, supporting audits, and testing spreadsheet controls to mitigate risk and ensure compliance.

Lead pre-sales solution design for enterprise clients: gather requirements, produce technical proposals, cost/effort estimates, high-level designs, and statements of work. Support sales and delivery teams, enable CX and cloud-native architectures, and expand into AI, automation, and data-driven solutions.

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

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.

Serve as a client-facing support engineer for a fintech SaaS platform, triaging and resolving issues, using AI tools to enhance responses, logging and escalating tickets in Jira, executing basic corrective actions, and driving change requests from recurring feedback.

Perform part-time remote data tasks to improve Spanish (Mexico) AI outputs: collect, evaluate, annotate, and tag content across audio, video, images, and other data; perform pairwise comparisons and counting tasks. Flexible schedule, immediate start.

Design, build, and productionize stateful autonomous AI agents for a WhatsApp fintech product. Implement LLMOps, observability, containerized deployments, evaluation pipelines, performance/cost optimizations, and mentor junior engineers.

Design, build, and scale production-grade, stateful autonomous AI agents; integrate agents into payments, fraud, and core product systems; implement LLMOps, observability, and evals-as-code; optimize RAG/vector DB pipelines for performance and cost; handle containerization, CI/CD, and post-launch stability; mentor engineers and drive best practices.

The AI Engineer will design, build, and scale autonomous AI agents, optimizing LLM capabilities and integrating them into the product, ensuring functionality across financial services.

Design, build, and scale production-grade, stateful autonomous AI agents for a WhatsApp-based fintech. Implement LLMOps, observability, RAG/vector DBs, containerized deployments (Docker/Kubernetes), eval pipelines, cost/performance optimizations, and mentor engineers to ship robust, tested agentic systems integrated with payments, fraud, and core product infrastructure.

Design, build, and scale production-grade, stateful AI agent systems integrated into core product flows. Implement LLMOps, observability, containerized CI/CD deployments, RAG/vector DBs, evaluation pipelines, performance/cost optimizations, and mentor junior engineers.

The role involves developing full-stack applications for mental healthcare, utilizing TypeScript, Node.js, React, and AI tools. Candidates will own features end-to-end and collaborate with teams to enhance user experience and system performance.