Top Artificial Intelligence Jobs in Mexico

Lead design, build, and operation of scalable, secure AI-enabled platforms; mentor engineers; ensure reliability, security, and delivery of conversational AI and cloud-native solutions; collaborate cross-functionally to translate use cases into platform capabilities.

Lead and develop seven Data Specialists in Mexico City, ensuring high-quality customer data services, strong communication, and responsive delivery. Own team metrics, quality reviews, capacity planning, and operational priorities. Coach team members through complex data challenges, lead strategic efficiency initiatives and AI adoption, and collaborate with Sustainability Advisory, Customer Success, and Project Management. Help establish an inclusive, high-performance culture across the Mexico City office.

The AI Engineer will prototype Generative AI tools, automate processes, ensure integration with enterprise systems, and enforce compliance while fostering AI literacy across teams.

Execute day-to-day Agency & Trust operational processes for LATAM clients, interpret complex client contracts, ensure timely transactional processing, maintain control logs and evidence, perform collateral and disbursement workflows, and develop verification/checking skills to validate junior work and ensure compliance with contractual and regulatory requirements.

Design and build AI agents, skills, and automation for software development workflows, including test generation, code review, and CI feedback. Improve local development environments, test performance, and internal engineering tools. Partner cross-functionally with engineers to adopt AI-assisted workflows, evaluate emerging AI capabilities, and reduce development friction through practical, useful solutions.

Manage healthcare data partners from qualification through sample evaluation, activation, deal structuring, and ongoing engagement. Conduct discovery and due diligence, coordinate NDAs and sample intake, assess and tier partners, socialize data assets internally, support pricing and statements of work, and facilitate transitions into operations. Develop portfolio growth strategies, maintain partner relationships, identify market opportunities, systemize workflows, and use deal activity and market signals to improve partnership scalability.

Lead design, development, and deployment of AI/ML solutions for manufacturing: create models for optimization, predictive maintenance, quality analytics; build data pipelines, scalable architectures; apply computer vision, NLP, and time-series methods; integrate with production teams; mentor engineers and drive Industry 4.0 initiatives.

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.

As an AI Engineer, you will develop generative AI tools, automate processes, ensure AI system integration, and promote AI literacy across teams.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Process customer purchase orders while improving order-entry accuracy, efficiency, and data quality. Analyze workflows, build Python, SQL, database, Power Automate, and other digital solutions, and explore AI and cloud technologies to automate repetitive tasks. Partner with Sales, Engineering, Operations, Customer Support, and Digital teams to resolve issues, standardize processes, support cybersecurity and data governance, and drive continuous improvement at ABB’s San Luis Potosi plant.

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.

Lead data architecture, engineering, integrations, and analytics for AI-enabled life sciences products. Partner with platform, product, solutions engineering, and client services teams to modernize data systems, deliver standard and customized analyses, and generate product and customer insights. Manage and mentor data analysts and engineers while scaling a high-fidelity, accessible, AI-ready data platform.

Coordinates operational execution through structured reporting, system updates, risk and support tracking, stakeholder coordination, and accurate data maintenance. The role prepares reports and documentation, manages multiple priorities, supports strategic decision-making, operates AI tools, and collaborates with SRM, Operations, and global cross-functional teams.

Own the full B2B sales cycle across LATAM, from prospecting and discovery through proposals, negotiation, and closing. Engage CFOs and finance leaders, diagnose financial operations challenges, quantify ROI, position Paystand’s automation solutions, and build qualified pipeline. Use AI tools for research, outreach, preparation, follow-up, and deal coaching. The role is onsite in Guadalajara, conducted primarily in Spanish, and requires advanced professional English proficiency with regional client travel as needed.

Analyze HR and people data to create clear narratives, reports, and dashboards that support business decisions. Partner with HR, IT, and data strategy stakeholders on scalable reporting solutions and AI-driven analytics initiatives. Maintain data accuracy, document automated workflows, translate business requirements, and communicate insights effectively to technical and business audiences.

Leads product strategy and operations for consumer lending, partnering with the Head of Consumer Lending to align squads, manage roadmaps and OKRs, optimize product processes, and improve lending funnel conversion, adoption, retention, and delivery. The role coordinates Product, Engineering, Risk, Data, Legal, and Compliance teams while establishing experimentation, feedback, and go-to-market frameworks in a high-growth fintech environment.

Own the multi-year strategy for Felix’s reusable lending platform, including sponsor-bank integrations, loan management, underwriting, servicing, and money movement. Make build-versus-buy and reusable-versus-custom decisions, establish platform processes, and lead cross-functional initiatives across engineering, risk, compliance, finance, and external partners. The role requires deep understanding of financial system integrations, regulated environments, architectural trade-offs, and 0-to-1 product development, with responsibility to build a team as the platform scales.

Leads product strategy and operations for consumer lending, partnering with the Head of Consumer Lending to define roadmaps, align product squads, manage OKRs, optimize delivery processes, and drive experimentation, adoption, retention, and funnel performance. Coordinates Product, Engineering, Risk, Data, Legal, Compliance, and external partners while establishing product feedback loops, rollout frameworks, and go-to-market readiness.

Leads enterprise sales strategy and revenue growth for Epiq’s AI-powered eDiscovery, legal technology, compliance, analytics, and information governance solutions. Develops pipelines, manages complex consultative sales cycles, expands strategic accounts, and engages executive stakeholders across corporations, law firms, government, and regulated industries. Acts as an AI and legal technology subject matter expert, supports responsible AI adoption, partners cross-functionally on solution development and delivery, and represents Epiq through market development, thought leadership, and strategic partnerships.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

Lead hands-on design and delivery of production-ready agentic AI applications and platform capabilities. Drive architecture, SDLC best practices, observability, security, and automation. Collaborate with Applied AI, Product, and Platform teams to move projects from prototype to governed production while mentoring engineers and improving developer productivity using AI-enabled tooling.

Develop and operationalize AI and analytics solutions using Palantir Foundry, machine learning, data modeling, data mining, and visualization. Partner with Finance and Lead Gen stakeholders to translate business needs into scalable workflows, validate results, improve data quality, and measure model performance. Document model logic and implementation details while collaborating across technical and business teams.