Top Artificial Intelligence Jobs in Mexico City

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.

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.

Build and operate production GenAI features and shared AI infrastructure, including RAG pipelines, LLM personalization, conversational agents, agentic workflows, evaluation frameworks, guardrails, MLOps, and observability. Own features from specification through deployment and on-call operations, evaluate model quality, integrate AI applications with business tools, document decisions, and mentor engineers.

Own Hightouch’s core marketing product portfolio, including audiences, analytics, experimentation, trait building, and orchestration. Set product vision and priorities, lead 0-to-1 innovation, improve adoption, and drive revenue outcomes. The role requires close collaboration with Engineering, Design, executives, customers, and go-to-market teams. This senior, hands-on product leadership position involves managing multiple workstreams, validating market needs, defining MVPs, and presenting product strategy and customer insights.

Own and negotiate Firecrawl’s commercial agreements, including enterprise contracts, data licenses, vendor agreements, NDAs, and partnerships. Advise sales, business development, product, and engineering on data rights, privacy, security, intellectual property, indemnification, and liability. Build legal templates, playbooks, fallback positions, and approval processes while supporting compliance initiatives. Operate autonomously, escalate novel issues appropriately, and provide practical business-focused legal guidance in a fast-moving AI infrastructure company.

Design and lead scalable AI architectures for enterprise customer experience solutions. Translate AI capabilities into measurable business outcomes, build reusable frameworks and prototypes, align product and engineering, drive adoption, and establish lifecycle best practices including deployment, monitoring, governance, and optimization.

Leads product growth and digital insights for a business application, owning local product strategy, roadmap prioritization, discovery, requirements, and stakeholder alignment. Manages an AI and machine learning personalization squad developing recommendation, cross-sell, and upsell models. Owns data management, analytics, experimentation, impact measurement, and business insights to support data-driven decisions. The role bridges business, technology, and data teams across regional environments.

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.

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.

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.

Own the post-sale customer journey from implementation through adoption, renewal, and expansion. Configure AI agents, workflows, prompts, integrations, call routing, notifications, and automation rules. Lead onboarding and implementation calls, troubleshoot technical issues, coordinate with engineering, identify churn and growth opportunities, and create playbooks to improve recurring implementation processes. Manage multiple B2B software customers while delivering measurable ongoing value.

Leads full-stack engineering projects through hands-on development and coordination of internal and external resources. Provides production support for financial and operational systems, designs architectures, develops APIs and frameworks, and builds CI/CD pipelines. Performs data analysis and reconciliations, while integrating LLMs and AI-assisted workflows into internal tools, research pipelines, and developer tools.

Develop and support financial systems, dashboards, trade feeds, risk platforms, operational tools, and accounting systems. Design and implement APIs, frameworks, architectural improvements, and CI/CD pipelines. Analyze and reconcile data, lead engineering contributions, coordinate internal and external resources, and integrate LLMs and AI-assisted workflows into internal tools, research pipelines, and developer tooling.

Lead the architecture and development of full-stack AI applications, including Python backend services, modern frontend interfaces, data pipelines, agentic workflows, and LLM integrations. Make technical decisions, conduct code reviews, mentor developers, establish engineering best practices, and collaborate with product, design, and QA teams. Advise stakeholders on emerging AI and web technologies while delivering scalable solutions for client projects.

Leads data engineering, Palantir Skywise architecture, and AI solution development for Airbus manufacturing and operational environments. Builds scalable pipelines, analytical workflows, machine learning and generative AI applications, and enterprise data foundations. Oversees Alteryx and Tableau platforms, establishes governance, mentors technical teams, translates business challenges into data products, and supports AI Center of Excellence initiatives. The role is onsite 60% across several U.S. locations and requires approximately 10% travel.

Create and optimize AI-assisted marketing content, social media assets, website materials, and campaigns. Improve GEO, AEO, SEO, and AI search visibility; monitor competitors and content gaps; build marketing reports; analyze KPIs; automate workflows; and support website updates. The role requires strong marketing judgment, creativity, independent project ownership, and effective collaboration with marketing, sales, and leadership teams in a remote environment.

Leads business analysis for enterprise software products hosted on Microsoft Azure. Elicits and documents requirements, creates user stories and acceptance criteria, supports Scrum delivery and backlog refinement, analyzes enterprise processes and integrations, and partners with product, engineering, architecture, and UX teams. Helps define AI-enabled capabilities, including intelligent search, conversational interfaces, agents, and automation, while addressing responsible AI, governance, security, and business outcomes.

Conduct approximately 50 outbound calls daily to US tax and accounting decision-makers, generate and qualify at least 10 opportunities monthly, manage pipeline activity in Salesforce, follow established sales methodologies, collaborate with Account Executives on lead handoffs, and participate in coaching. The role requires selling SaaS solutions powered by data and AI to CPAs and tax professionals.

Build and ship production software in client technology stacks, including APIs, services, data models, interfaces, automated tests, CI/CD, and failure handling. Use AI coding agents daily while reviewing all generated code. Work with relational and non-relational databases, third-party integrations, cloud deployments, infrastructure as code, and compliance requirements. Collaborate directly with clients in English and deliver maintainable, tested software end to end.

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.

As a Lead Software Engineer for AI, you will develop AI-powered systems, focusing on backend services, scalable production systems, and collaboration with cross-functional teams to deliver intelligent solutions.

Join a small cross-functional team to design, build, and operate an LLM-powered agent platform: orchestration, tool integrations, APIs, knowledge/memory infrastructure, trust & safety, evaluation/testing, and partner with Operations to translate workflows into automation. Mentor other engineers and deliver production-ready systems.

Leads the Advanced Manufacturing Engineering team and molding technology strategy for composite blade manufacturing. Directs process development, testing, validation, industrialization, automation, data analysis, technology roadmaps, supplier performance, and capital planning. Oversees molding processes including mold preparation, gel coat, fiber layup, resin infusion, curing, and bonding. Develops engineers, manages project portfolios, ensures technical documentation and change control, and drives safety, quality, cost, productivity, and operational excellence improvements.

Develop product positioning, messaging, content, and go-to-market assets for an AI training data platform. Lead end-to-end product, vertical, DataLab, and commercial launches; translate complex AI and data concepts for technical buyers; create thought leadership, case studies, decks, webinars, videos, social content, and landing pages; and partner with Product, Sales, DataLab, Community, and business leaders to strengthen market narrative and support commercial growth.

Design, build, deploy, and support production AI agents and automations for customer workflows. Responsibilities include workflow discovery, solution scoping, Python and SQL development, third-party integrations, browser automation, testing, monitoring, error handling, secure multi-tenant deployment, and operational handoff. The role also trains operations teams, troubleshoots production issues, measures customer impact, and develops reusable deployment components.