Top Artificial Intelligence Jobs in Mexico

The Senior AI Engineer will design and develop production-grade AI systems, focusing on LLM integrations, ML model serving, and backend reliability for Jeeves's financial platform.

Design, build, and deploy bespoke AI/LLM-driven solutions on the Salesforce platform. Handle end-to-end delivery including data modeling, integration, agent orchestration, debugging, prototyping, and client-facing implementation and optimization.

Embed with business teams to rapidly prototype, build, and ship AI-powered workflows: prompt layers, automations, lightweight agents, RAG, and API integrations. Translate workflow assessments into deployable solutions, run UAT, document handoffs, and feed learnings back to the AI Program Office.

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.

Lead operational excellence for enterprise AI/ML platforms: ensure reliability, scalability, observability, governance, and deployment readiness. Build automation, CI/CD, IaC, monitoring, and model lifecycle processes. Serve as senior escalation for incidents, drive root cause analysis, mentor engineers, and partner across Data, Infrastructure, Security, and Product teams to enable production AI workloads and generative AI adoption.

Design, build, and optimize high-performance AI infrastructure systems to support intelligent agents, ensuring reliability and scalability for millions of users.

As an AI Engineer, you will build LLM systems, maintain AI solutions, collaborate across teams, and refine infrastructure integration while ensuring system uptime and accuracy.

The role involves developing full-stack features swiftly, utilizing AI tools for coding, managing front and backend systems, and ensuring production quality through testing and CI.

Design, deploy, and optimize AI-driven agents and automated workflows across business functions. Identify inefficiencies, build tool-using and multi-agent systems, integrate advanced LLM tools, collaborate cross-functionally, document processes, and continuously test and refine automations to drive scalable operational efficiency.

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.

Lead end-to-end delivery of AI-enabled products as a hands-on Technical Project Manager and business analyst: scope, schedule, documentation, UAT, governance, KPI tracking, and automation to accelerate engineering throughput and stakeholder alignment.

The AI Enablement Lead will design and conduct training programs to improve AI fluency within Juniper Square, focusing on tools like Claude and Cowork. Responsibilities include curriculum development, leading sessions, coaching, and measuring adoption outcomes.

Lead engagement with business teams to develop AI-driven internal applications, managing everything from discovery to production and ensuring high adoption post-launch.

As an AI Consultant, you'll drive customer adoption of AI features, implement AI products, analyze performance metrics, and provide training initiatives for clients. You'll collaborate with various teams to enhance customer experiences and ensure successful adoption of Glia's AI technologies.

The role involves designing, building, and optimizing an AI-driven lead generation and conversion system for a premium concierge medical practice, integrating multiple platforms and ensuring continuous optimization.

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.

Lead order management alignment across business units, govern prioritization frameworks, manage escalations, and coordinate supply-constrained allocations. Analyze backlog and supply signals to drive execution, provide stakeholder updates, and implement continuous improvements and reporting to optimize fulfillment and revenue outcomes.

Design and maintain backend services, develop microservices, implement asynchronous processing, and collaborate on system scalability for AI-assisted applications.

The Senior Full Stack Engineer is responsible for developing backend services with Node.js and mobile applications using React and Capacitor, emphasizing code quality and architectural principles in a collaborative environment.

Design and maintain cross-platform mobile applications for iOS and Android, optimize app performance, manage deployments, and collaborate with various teams.

Design, develop, and maintain serverless applications on AWS, manage infrastructure as code, collaborate with teams, and enhance CI/CD processes.

Design and build AI-driven automation and internal tooling to replace manual workflows, improve reliability, and scale IT/platform operations. Implement APIs, event-driven services, and CI/CD; apply LLMs for decision support and incident analysis; maintain systems with testing, observability, and on-call participation while collaborating with Security, Compliance, and Platform teams.

The QA Automation Engineer will enhance testing processes, collaborate with teams to build automated frameworks, and support modern software delivery in a cloud-native environment.

Develop and expand a model zoo for CNNs, LLMs and VLMs: implement models in Python/C++, build inference/benchmarking pipelines, automate testing and CI, optimize performance on NPU accelerators, and produce demos.

Lead design and evolution of scalable, secure cloud-native SaaS platforms using C#/.NET. Define architecture standards, champion microservices, DDD, CQRS, event-driven and API-first approaches, mentor engineers, improve performance, observability, and security, and integrate AI-assisted development tools and workflows across teams.