Top Artificial Intelligence Jobs in Mexico City

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.

Develop and improve AI-powered conversational systems for the Collections team. Responsibilities include researching, experimenting, validating, launching, and monitoring AI systems; applying text analytics, NLP, sampling, and conversational analysis; engineering prompts; evaluating language models and RAG systems; conducting A/B tests; and building automated tests for conversational agents. The role also requires investigating issues, documenting findings, monitoring quality metrics, and communicating technical results clearly.

Review high-volume NDAs, master services agreements, and vendor contracts using AI-assisted workflows and client-specific legal playbooks. Verify and correct AI-generated markups, identify confidentiality and commercial risks, escalate non-standard terms, maintain accurate ticket statuses, and ensure timely, accurate handoffs to quality control. The role requires independent remote work, strong legal judgment, and experience reviewing contracts under U.S. or U.K. law.

Manage Lynx’s Brazilian marketing strategy by localizing global messaging, executing B2B demand generation campaigns, coordinating industry events, creating commercial content, managing social media, and supporting Sales and Pre-Sales. The role owns vendor coordination, competitor monitoring, brand consistency, and performance measurement through pipeline, lead, event, and engagement metrics. It requires strong knowledge of Brazil’s fintech and financial services market, autonomous execution, executive communication, and occasional travel across Brazil and Latin America.

Design, develop, deploy, and maintain intelligent automation solutions using Microsoft Power Platform, Azure AI, Copilot technologies, RPA, APIs, and enterprise applications. Build AI-powered workflows, autonomous agents, and digital assistants for document processing, email triage, content generation, summarization, and decision support. Apply governance, security, compliance, and Responsible AI practices while improving automation reliability, scalability, and operational efficiency across global logistics processes.

Leads and mentors an engineering team building scalable, reliable AI-powered solutions for PMG’s Alli marketing platform. Responsibilities include defining technical roadmaps, designing and deploying AI features, collaborating with product and cross-functional teams, guiding architecture and engineering practices, conducting code reviews, debugging, testing, and staying current with emerging AI and machine learning technologies.

Build enterprise Amazon Connect contact centers and conversational AI solutions using AWS, Amazon Bedrock, serverless services, TypeScript, Python, and React. Develop contact flows, AI agents, integrations, custom agent experiences, infrastructure as code, CI/CD, monitoring, and production support. Collaborate with customer engineering teams on technical decisions, releases, troubleshooting, migrations, and knowledge transfer.

Accelerate enterprise AI and automation adoption by designing workflows, developing Power Platform solutions, building Copilot agents, troubleshooting issues, delivering training and workshops, coordinating implementations, and promoting governance. The role supports business champions, translates requirements into technical solutions, facilitates UAT and rollouts, and builds an AI automation community while maintaining compliant, sustainable, production-ready standards.

Contractor role evaluating AI chatbots in Spanish (Latin America). Perform structured text and voice interactions with models, submit ratings, write-ups, screenshots or recordings, pass language and technical assessments, and complete identity verification. Flexible, task-based work paid hourly.

Lead architecture and development of AI-first backend systems and orchestration for Audit Suite. Drive AI integration (LLMs, retrieval, vector stores), ensure scalability, reliability, observability, and compliance. Mentor engineers, lead cross-functional initiatives, shape roadmap and platform integration, and implement high-throughput, low-latency AI workflows across heterogeneous stacks.

Build cloud and endpoint discovery capabilities for AI agents, assess their configurations, access, and security risks, and integrate findings into Delinea’s identity and attribution platform. The role requires backend development experience with cloud provider APIs, asset inventory systems, and existing platforms. Candidates should be able to solve ambiguous technical problems independently and may have experience with endpoint management, CSPM, CIEM, or AI agent authentication.

Build AI security capabilities into Delinea’s access proxy and cloud platform. Develop gateway controls for AI agents, MCP, agent-to-agent communication, just-in-time access, and request-path authorization. Connect existing proxy functionality to the Delinea Platform, validate it with customers, and migrate capabilities without disruption. Collaborate with product, proxy, and access-engine teams while making independent architectural and implementation decisions.

Build backend integrations connecting Delinea’s identity security platform with third-party AI ecosystems including Salesforce Agentforce, Microsoft Copilot, AWS, and Google Cloud. Develop connector and adapter patterns, retrieve native identity signals, support OAuth and token exchange, ingest webhook events, and govern AI agents through provider APIs and attestation. Contribute reusable discovery, identity, and policy capabilities while solving complex integration problems independently.

Leads the architecture and production delivery of AI-powered solutions across technology teams. Designs scalable AI workflows, integrations, observability pipelines, evaluation frameworks, guardrails, and governance standards. Evaluates LLM platforms and agentic technologies, establishes reliability and compliance practices, partners with cloud, security, SRE, product, and data teams, and mentors engineers. Prototypes solutions hands-on and guides ambiguous use cases from concept through production.

Build and deploy AI-powered prospecting agents, SDR tools, lifecycle automations, onboarding flows, and internal products. Integrate CRM, marketing, sales, and LLM systems using automation platforms and code. Own lead scoring, routing, SDR-to-AE handoffs, and lifecycle personalization while measuring impact on pipeline, activation, retention, and CAC payback. Partner with Sales, Lifecycle, Data, and Engineering teams to rapidly prototype, validate, scale, or discontinue automation initiatives.

Build AI agent discovery across cloud platforms and endpoints, assess agent configurations, access, and security risks, and integrate findings into Delinea’s identity and attribution layer. The role involves extending existing discovery and inventory systems, partnering with platform teams, and designing backend solutions for Azure while expanding to AWS and Google Cloud.

Build and maintain BI dashboards, reporting tools, and automated data workflows. Analyze customer behavior, funnels, retention, engagement, and product adoption to deliver actionable insights across Product, Operations, Marketing, Finance, and Leadership. Use AI tools and APIs to improve analytics workflows, self-service exploration, data-quality checks, and insight generation while validating accuracy, privacy, and business impact.

Own Clara’s enterprise AI automation strategy and lifecycle, from identifying high-friction workflows through deployment, scaling, and impact measurement. Build AI-powered workflows with N8N and LLM APIs, create operational dashboards in Metabase, identify data gaps, and partner with Engineering on Databricks pipelines. Support product launches, establish AI operations best practices, document systems, and collaborate with senior leaders across Product, Sales, Finance, and Engineering.

Produce commercial image and video content using generative AI models, prompt engineering, model training, and internal tools. Collaborate with creative and post-production teams to integrate AI assets into campaigns, ensure brand consistency and quality, improve workflows, evaluate emerging models, document processes, and coach colleagues on AI techniques and tools.

Leads enterprise quality engineering and test automation strategy across UI, API, integration, performance, and data layers. Architects Java-based automation frameworks, integrates quality gates into CI/CD pipelines, drives ETL and data validation, and governs responsible AI adoption in QA. Mentors QA engineers, establishes standards and governance, leads transformation initiatives, and collaborates with Engineering, DevOps, Data Engineering, and Product teams.

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.

Build and support Klar’s AI capabilities through data quality maintenance, audits, validation, KPI reporting, process automation, and infrastructure development. Analyze data to support strategic decisions and communicate findings to technical and non-technical stakeholders. The role is hybrid and based in Mexico City.

Own outbound prospecting to senior finance leaders across Mexico and Colombia, creating multi-channel campaigns through email, LinkedIn, WhatsApp, and related channels. Use AI, automation, enrichment tools, and CRM workflows to improve research, prioritization, personalization, and follow-up. Build and test sales experiments, analyze conversion performance, optimize the sales stack, and document scalable playbooks. Partner with account executives, sales leadership, and RevOps to strengthen Clara’s outbound engine.

Lead generative AI and creative technology for Salesforce’s Mexico City creative team. Develop cinematic images and video, engineer prompting and generation pipelines, direct visual storytelling, oversee art direction and finishing, and maintain commercial-quality outputs. Test and document emerging AI tools, manage licenses, collaborate with creative teams, and accelerate production workflows across motion and static campaigns.