Top Artificial Intelligence Jobs in Mexico

Own private capital financial data operations, ensuring accurate, timely, and high-quality client data. Use AI-assisted extraction and validation tools, investigate exceptions, improve quality frameworks, automate workflows, and strengthen operational controls. Partner with Product, Engineering, Data Operations, and Client Service teams to improve processes and client outcomes. Mentor junior colleagues, analyze KPIs, communicate insights, and drive continuous improvement across AI-enabled financial data operations.

Manage AI project plans, timelines, teams, risks, dependencies, governance, milestones, dashboards, communications, pilots, and launches. The role supports AI strategy and transformation across hybrid operations in Mexico, Colombia, and Brazil, requiring program leadership, advanced English, and familiarity with AI, automation, digital products, analytics, CRM, Power Platform, or Microsoft Copilot.

AI intern supporting the integration of LLMs, agentic workflows, MCP server automation, prompt engineering, and AI-assisted development into business processes. Responsibilities include testing AI tools, building scripts and internal prototypes, supporting Agile and DevOps adoption, analyzing datasets, documenting findings, gathering requirements, and collaborating with engineering, operations, delivery, QA, finance, and support teams to improve efficiency and decision-making.

Leads risk-based IT, cybersecurity, privacy, operational technology, and integrated audit engagements from planning through reporting. Evaluates technology risks, controls, cloud environments, enterprise applications, security frameworks, privacy practices, third-party providers, and emerging technologies. Partners with business and technology leaders to identify risks, develop recommendations, support enterprise audit planning, and improve governance. Guides audit team members, communicates findings to management, and drives sustainable risk mitigation across global operations.

Leads enterprise technology strategy, delivery, and transformation across Finance, FinTech, Legal, and Risk. Oversees product platforms, Agile and DevOps adoption, AI and data initiatives, digital transformation, change management, vendor partnerships, governance, and technology operations. Partners with executive stakeholders to align global priorities, integrate platforms, manage dependencies, and deliver scalable, secure, value-driven outcomes across a federated enterprise technology organization.

Develops and supports AI-enabled HR solutions, conversational agents, workflow automation, and enterprise integrations. Responsibilities include preparing and transforming data, building and testing AI applications, supporting deployment and monitoring, and contributing to responsible AI governance. The role works with AI engineers, product owners, HR stakeholders, and technology teams in an Agile environment while building foundational expertise across the AI solution lifecycle.

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.

Build and operate production AI infrastructure powering intelligent agents at scale. Develop high-performance Rust services for model inference, orchestration, and execution; design scalable distributed systems; establish MLOps, observability, guardrails, and failure recovery; and optimize latency, throughput, reliability, and cost. Partner with agent systems and infrastructure teams to turn prototypes into hardened services serving millions of users.

Lead hands-on architecture for reusable Fabric platform products and services across cloud, APIs, data, security, UX, and AI-enabled engineering. Develop architecture blueprints, guide implementation, review code, prototype solutions, establish engineering standards, and balance cost, risk, quality, security, and delivery speed. Partner with product, engineering, security, and architecture teams to create scalable, secure, observable, maintainable, and reusable platform capabilities.

Leads PayJoy’s global Lock Operations function, developing strategy, takedown tooling, and operational processes to reduce lock exploit losses. Coordinates fraud, risk, engineering, and legal stakeholders; measures disruption and value protected; provides technical intelligence to Fraud; and manages two specialists and an analyst while handling high-impact takedowns.

Lead the design, development, and deployment of scalable machine learning, generative AI, and LLM solutions. Build RAG, conversational AI, summarization, enterprise search, and knowledge retrieval applications; optimize model performance, cost, latency, and reliability; and support MLOps pipelines. Partner with stakeholders to identify business use cases, lead proofs of concept, shape AI strategy and governance, and mentor AI engineering teams.

Designs and deploys secure AWS cloud architectures, leads enterprise migrations and application modernization, and builds Generative AI and machine learning solutions using Bedrock, SageMaker, vector databases, and RAG. Acts as the primary technical leader for client engagements, advises executive stakeholders, develops proofs of concept, drives AWS adoption and account growth, and mentors engineering teams while creating reusable infrastructure and delivery frameworks.

Build and operate backend services, APIs, data stores, and cloud infrastructure for Zendesk’s internal AI platform. Create reusable integration, deployment, governance, and release patterns for AI assets; guide teams from prototypes to production; and ensure secure, observable, supportable systems. Own CI/CD, infrastructure as code, testing, incident response, documentation, architecture reviews, and cross-functional collaboration with product, security, identity, and enterprise AI teams.

Design, develop, test, and deploy production AI and machine learning applications, including LLM features, RAG pipelines, agent workflows, predictive models, and automation. Build data pipelines, integrate AI solutions with enterprise platforms, monitor production performance, and improve deployed systems. Collaborate with product, data, business, and engineering teams while documenting architectures and following responsible AI practices.

Develop machine learning and AI solutions for recommendation, personalization, segmentation, behavioral analysis, churn prediction, and notification optimization. Perform exploratory and statistical analysis, feature engineering, model evaluation, and scalable implementation using large datasets. Collaborate with Product, Engineering, and Business teams to translate challenges into data products and communicate actionable insights to technical and non-technical stakeholders.

Leads hands-on operations for AI and ML platforms across Azure and AWS. Builds observability, automation, AI-augmented incident tooling, runbooks, and operational readiness processes. Handles complex incidents, root-cause analysis, post-mortems, platform onboarding, and continuous toil reduction. Partners with engineering teams on operability and technical improvements while mentoring L1 operators and junior SREs. Requires strong SRE, cloud infrastructure, scripting, observability, and automation expertise.

Leads hands-on AI/ML platform operations across Azure and AWS. Designs observability, telemetry, alerting, automation, and AI-augmented incident tooling; manages complex incidents, root-cause analysis, post-mortems, operational readiness, and platform onboarding. Partners with engineering teams to improve operability, mentors L1 and L2 engineers, reduces operational toil, and drives continuous improvement across a multi-tier SRE organization.

Evaluate AI chatbots and language models through structured written and voice interactions. Assess capabilities, safety, helpfulness, and response quality, then submit ratings, write-ups, screenshots, or recordings according to project requirements. This fully remote, task-based contractor role requires Latin American Spanish fluency, strong English communication, AI model experience, reliable equipment and internet, and availability to start within 48 hours.

Mercor seeks research proposals examining AI’s economic and labor impacts, human-AI collaboration, productivity, enterprise adoption, and returns. Eligible applicants include researchers at universities, nonprofits, public benefit corporations, and small startups in the United States or United Kingdom. Applicants must submit an expression of interest describing methodology, team expertise, outcomes, timeline, risks, and budget. Selected projects must produce an openly licensed paper, dataset, methodology, or tool.

Analyzes, redesigns, and standardizes HR and People Care processes for AI and automation readiness. The role maps workflows, removes inefficiencies, defines business requirements and human-review controls, evaluates AI opportunities, measures operational value, and partners with HR, Legal, Compliance, HRIS, product, and technology stakeholders on implementation and continuous improvement.

Leads the design and development of scalable mobile and web test automation frameworks. Builds automated tests for Android, iOS, hybrid, and web applications; integrates testing into CI/CD pipelines; and applies AI tools to improve productivity, code quality, and testing workflows. Provides technical leadership, mentors engineers, establishes automation standards, collaborates with clients and cross-functional teams, and owns technical initiatives from design through implementation.

Build and optimize cloud-agnostic Databricks Lakehouse architectures and scalable ETL/ELT pipelines using Spark and Delta Lake. Integrate MLflow for AI model operationalization, implement CI/CD and Infrastructure-as-Code deployments, tune performance and cloud costs, and enforce data governance and security. Collaborate with architects, data scientists, engineering teams, and clients to deliver production-ready AI solutions and technical handoffs.

Leads transformation of MUFG’s Data Office by evaluating operating models, governance, processes, capabilities, and technology solutions. Develops future-state strategies, transformation roadmaps, business cases, executive communications, and measurable outcomes. Advises senior leaders, facilitates strategic decision-making, drives cross-functional initiatives, improves data governance and AI readiness, and leads organizational change across a complex financial services environment.

Develop and maintain full-stack web applications using TypeScript, React, Node.js, Express, PostgreSQL, AWS, and Docker. Build frontend components, backend APIs, and three-tier architecture solutions; troubleshoot issues across application layers; contribute to architecture, CI/CD, code reviews, and development best practices. Collaborate autonomously with distributed teams in Mexico and the United States. Advanced English proficiency is required.

Drives talent acquisition process excellence across Latin America through process standardization, KPI and dashboard analysis, continuous improvement, technology adoption, change management, employer branding, recruitment marketing, and talent attraction initiatives. Partners with regional and global stakeholders to improve recruiting efficiency, candidate and hiring manager experience, workforce planning, and attraction outcomes.