Top Artificial Intelligence Jobs in Mexico

Build and own production AI systems, including an enterprise LLM application and internal agentic developer tools. Design backend services, APIs, infrastructure, agent workflows, evaluations, and automated testing. Manage deployment, monitoring, debugging, reliability, latency, and cost optimization while collaborating with engineering and product teams to establish scalable AI architecture and reusable development patterns.

The AI Developer will design, train, optimize, and deploy LLM models, develop backend services and maintain models in offline environments, focusing on ML engineering and optimizing workflows.

Leads customer-facing computational biology and bioinformatics engagements from strategy through delivery. Develops scalable multi-omics analyses, integrates pipelines, statistical models, machine learning, and heterogeneous datasets, and generates insights for drug discovery, biomarker identification, indication selection, and patient stratification. Manages project scope, resources, milestones, governance, stakeholders, and delivery challenges while supporting proposals, scientific presentations, thought leadership, and mentoring.

Responsible for general accounting, journal entries, reconciliations, account analysis, payroll and expense tracking, financial close activities, and internal and external audit support. The role also analyzes financial information, ensures accurate reporting, and improves finance processes through automation, data analysis, and artificial intelligence tools. Knowledge of accounting principles, ERP systems, Excel, US GAAP, and IFRS is beneficial.

Leads a 45-person employee organization and 50 contractors responsible for USAA’s telematics application strategy, architecture, engineering delivery, vendors, budgets, security, compliance, and modernization. Oversees cloud, mobile, data, AI, machine learning, IoT, and connected-vehicle capabilities supporting insurance pricing, underwriting, claims, fraud detection, and member engagement. Partners with business and technology executives on roadmaps, technical debt reduction, SDLC controls, risk management, and ecosystem relationships.

Develop and maintain pricing models for accident and health products across Latin America using Radar. Analyze internal and external data, prepare rate reviews, monitor pricing variables and profitability, improve pricing standards, and ensure data quality. The role partners with IT and Commercial teams, supports data cleanup and restructuring, and provides pricing insights and monitoring recommendations to the A&H Manager.

Build and deploy production software for Clara’s B2B fintech platform. Engineers own features end to end, including design, coding, testing, deployment, monitoring, and maintenance. Depending on track, work involves backend services and APIs or data pipelines, machine learning models, risk scoring, fraud detection, and spend intelligence. The role emphasizes AI-native development, strong technical fundamentals, ownership, cross-functional collaboration, and learning complex fintech and regulatory domains.

Execute large-scale projects for AI labs and technology companies, managing expert networks, multimillion-dollar portfolios, delivery quality, operational issues, customer communication, and process improvements. The role requires analytical problem-solving, prioritization, ownership, and comfort with ambiguity while collaborating across operations, engineering, and machine learning teams. Candidates may be recent graduates and will work remotely from Mexico City before transitioning to an in-person model.

Leads distributed engineering teams delivering enterprise applications, APIs, integrations, cloud-native AWS solutions, microservices, and AI-enabled applications. Oversees technical direction, people management, modernization, API governance, data architecture, Agile delivery, DevSecOps, and engineering excellence. Partners with business, product, architecture, and operations stakeholders while ensuring scalable, secure, compliant solutions aligned with healthcare requirements.

Human Resources intern supporting the development and implementation of HR systems. The role requires advanced computer skills, including Power BI, Windows, and AI tools, along with proactive problem-solving, continuous improvement, teamwork, flexibility, and the ability to work under pressure while meeting quality and performance objectives.

Intern supporting the development and implementation of Human Resources systems. The role requires advanced computer skills, including Power BI, Windows, and artificial intelligence tools, along with proactive problem-solving, teamwork, adaptability, and the ability to work under pressure while meeting objectives.

Lead design, build, and productionization of GenAI solutions and traditional full-stack applications. Scope use cases, engage stakeholders, mentor developers, manage roadmaps, ensure security/compliance, and operate deployed systems with continuous improvement.

Create and manage high-quality Spanish and English content across LinkedIn, blogs, websites, video, executive communications, and social channels. Own content projects from concept through publication, collaborate with design and cross-functional teams, monitor internet trends, and maintain high editorial standards. Use AI-native workflows, N8N or custom GPTs, and automation to improve content production. The role also supports video content, leadership communications, B2B fintech storytelling, and performance analysis.

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.

Supports risk strategy for one to two credit portfolios by monitoring profitability and risk KPIs, preparing analyses, documenting recommendations, coordinating strategy rollouts, and implementing risk controls. Uses SQL, R, or Python for data extraction, manipulation, modeling, forecasting, and statistical analysis. Partners with Data Science on machine learning and AI models and applies A/B test recommendations to credit policies while communicating findings to stakeholders.

Supports development, testing, validation, and operationalization of AI-driven data pipelines for private-markets analytics. Responsibilities include tuning AI/ML models, structuring heterogeneous data from SQL, documents, and Excel, conducting backtests and scenario analyses, integration testing, documenting requirements, automating analytical workflows, and writing advanced SQL queries. The role requires foundational Python, data-quality discipline, collaboration, and quantitative analytical skills.

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.

Leads a global multidisciplinary AI/ML team while remaining hands-on in architecting, developing, deploying, evaluating, monitoring, and governing production AI solutions. Applies traditional machine learning, deep learning, LLMs, RAG, and agentic AI to complex business problems. Partners with product, engineering, data, platform, and business teams; establishes responsible AI practices; and communicates technical strategy, risks, milestones, and outcomes to senior stakeholders.

Designs and improves chatbot processes, routing users to business experts and increasing bot engagement. Analyzes feedback to enhance the user experience, collaborates with cross-functional teams to maintain accurate bot information, and provides customer support through automated systems.

Architect and evolve backend systems, scalable APIs, AI-assisted services, and full-stack SaaS features. Build React interfaces, agent-driven development workflows, internal engineering tools, and AI-native coding practices. Own features end to end, optimize performance, and help establish engineering best practices while potentially leading a small team. The role emphasizes autonomy, asynchronous collaboration, and leveraging Claude Code, Codex, and other AI tools.

Develop and support enterprise applications using Java microservices, Angular, RESTful APIs, and modern AI development tools. Lead software development across analysis, design, coding, testing, deployment, and ongoing support. Build Gen AI and Agentic AI implementations, automate CI/CD quality and testing processes, assess application risks, and advise stakeholders. Provide technical guidance to junior analysts while applying financial-industry knowledge across wealth management, retail banking, CRM, investment products, and back-office operations.

Senior Business Analyst serving as a bridge between business, product, architecture, engineering, and operations teams. Responsibilities include requirements gathering, user stories, process modeling, Agile ceremonies, system and data-flow analysis, Azure-based platform evaluation, and defining requirements for AI-powered features involving LLMs, Copilot, and RAG. The role requires strong technical analysis, enterprise software experience, stakeholder facilitation, and advanced English and Spanish communication skills.

Lead a team of AI/ML, backend, and platform engineers building payment-routing optimization and LLM-powered products. Guide ML lifecycle and AI workflow architecture, oversee low-latency inference services, and maintain AWS, CI/CD, observability, and PCI-DSS standards. Own delivery planning, technical quality, hiring, coaching, and team development while partnering with product, operations, modeling leadership, and executives.

Build and own backend services, APIs, data models, and algorithmic or AI-driven business logic using Python and Django. Responsibilities include designing relational schemas, implementing RESTful endpoints, optimizing queries and performance, applying caching, translating product ideas into technical designs, and contributing to engineering patterns within a distributed startup team.

Own end-to-end delivery of complex AI client projects, translating evolving requirements into project scopes, delivery plans, and successful human data programs. Manage client relationships, cross-functional coordination, risks, quality, timelines, budgets, profitability, and delivery metrics. Partner with Sales, Operations, Product, and Engineering while improving scalable processes for AI project execution.