Top Artificial Intelligence Jobs in Mexico

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.

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.

Design, develop, test, deploy, and maintain RPA automation and AI agent solutions (e.g., Copilot Studio). Build integrations with ERP, MES, OA and other systems, optimize workflows for stability and efficiency, produce technical documentation and training, and provide user support.

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.

Translate customer priorities into secure, scalable Microsoft Azure infrastructure, data, and AI solutions during pre-sales and delivery. Lead discovery, shape proposals and SOWs, define staffing, plan governance, implement Azure Infrastructure AI solutions, ensure security/compliance and Responsible AI, promote reusable IP, and mentor teams while driving Azure adoption and operational readiness.

Coordinate day-to-day social publishing for major entertainment brands across YouTube and other social networks. Responsibilities include scheduling, quality assurance, community management, stakeholder coordination, approvals, content research, reporting, escalation, and process improvement. The role emphasizes careful review of AI-assisted work, publishing accuracy, platform updates, and reliable execution across multiple accounts and deadlines.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

Design, deploy, and maintain enterprise AI agents using BotDojo and approved AI tools. Gather requirements, engineer prompts, configure workflows, integrate agents with systems and databases, provide technical support and training, monitor performance, troubleshoot issues, maintain documentation, and ensure security, privacy, quality, and version-control standards.

Develop machine learning, NLP, and generative AI solutions for conversational analytics. Build scalable pipelines for conversational and unstructured data, design and evaluate LLM prompts, create sampling methodologies, and prepare data for Athena Studio workflows. Apply text analytics, classification, summarization, and pattern-recognition techniques while conducting experiments and communicating findings to technical and non-technical stakeholders.

Develop backend systems for 3D AutoReview, including geometry parsing, model analysis, quality detection, rule systems, scalable APIs, and AI-assisted review workflows. Collaborate with backend, frontend, product, and machine learning teams to deliver production features. Build extensible systems for custom 3D rules and reference data while experimenting with CAD, machine learning, and large language model technologies.

Design and implement AI-powered data pipelines and production workflows using LLMs, automation, and modern data engineering. Build systems that extract, clean, enrich, validate, and transform structured and unstructured data into customer-ready Excel, PDF, and Word outputs. Develop APIs and full-stack applications, optimize relational and vector databases, integrate AI orchestration frameworks, and translate prototypes into scalable enterprise solutions.

Develops AI-powered marketing intelligence and automation for creative and performance marketing. Automates reporting, competitive analysis, benchmarking, and insight generation; connects and queries data sources; validates AI outputs; identifies data-quality gaps; builds scalable AI workflows, agents, prompts, and reporting processes; evaluates emerging tools; and supports team adoption through documentation and training.

Design, build, deploy, and support scalable Go-based APIs and production agentic AI solutions. Collaborate with product, data science, and infrastructure teams to translate requirements, implement microservices on cloud (Azure/GCP), ensure reliability (SLOs, CI/CD), produce API documentation and partner enablement assets, and optimize cost, security, and operational readiness.

The Sr AI/ML Engineer will design and deploy machine learning models, build computer vision systems, and develop LLM-based features in a collaborative, fast-paced environment.

Early-career engineer role building AI-driven features, prototypes, and production-quality systems using modern AI coding agents. Work closely with founders and senior engineers to iterate fast, direct and evaluate AI agents, and contribute to AI infrastructure and agentic development workflows.

Lead development of AI-native production systems: convert AI-assisted prototypes into scalable, secure software; own architecture, reliability, and technical direction; direct and control AI coding agents; define engineering standards and workflows; collaborate with founders on product and strategy; debug complex issues and elevate engineering quality.

Create high-volume, high-quality marketing content using generative AI and AI agents (video, image, social). Develop timely campaign ideas, track AI and cultural trends, experiment with formats, and work closely with founders and the marketing team to shape brand voice and growth.

Design and build enterprise-grade AI solutions using AWS Bedrock, develop AI agents and RAG pipelines, integrate ServiceNow and SAP, create secure REST APIs and document-processing workflows, build React frontends, implement GenAI CI/CD and Responsible AI governance, and collaborate with engineering and business teams to scale AI-powered automation.

Design and build AI-powered IT help desk automation using AWS Bedrock and serverless tech. Develop AI agents for ticket triage, routing, IAM automation, REST integrations with enterprise systems, and scalable cloud-native architectures. Collaborate on architecture, integrations, and agent performance improvements.

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.

Build and maintain conversational AI agents for sales intelligence, integrating Salesforce, SharePoint, Snowflake, Databricks, and BigQuery. Develop semantic models, retrieval pipelines, vector indexes, data pipelines, and evaluation systems for trusted sales analytics. Partner with sales, finance, IT, security, and leadership teams to scope solutions, conduct demos, document capabilities, support governance, and drive user adoption. The role requires strong communication, Python and SQL skills, cloud data experience, and hands-on LLM or agent-building experience.

Architect and build production AI-powered HR systems using agentic workflows, multi-agent systems, APIs, and workflow automation. Integrate Workday and other HR tools, implement governance, audit logging, privacy controls, and human approval gates, and ensure reliable payroll-adjacent workflows. Document solutions, train People team users, drive adoption, and measure automation impact. The role requires strong software engineering, AI application development, HR technology, Workday, data privacy, and workflow automation experience.

Develop AI-enabled applications using .NET, C#, Azure, React, and CI/CD practices. The role requires at least six years of experience, practical AI knowledge, advanced English proficiency, and is fully remote.