Top Artificial Intelligence Jobs in Mexico City

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.

Support Mexico controllership by monitoring regulatory changes, maintaining internal controls, preparing local GAAP financial statement disclosures, supporting audits, and testing spreadsheet controls to mitigate risk and ensure compliance.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Build and operate Kraken’s internal AI platform, including governed integrations, authentication, internal tooling, evaluation systems, spend controls, identity and access controls, provisioning, vendor configuration, and policy enforcement. Provide technical enablement through documentation, deep dives, and office hours while supporting teams and administering the enterprise AI estate.

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.

Analyzes human-generated data quality across AI programs using SQL, Python, statistical methods, and hands-on annotation review. Investigates quality issues, identifies failure patterns, measures impact, and develops recommendations. Supports quality pipelines, automated validations, rubrics, gold sets, calibration exercises, reporting, and dashboards. Collaborates with quality engineering, operations, delivery, and engineering teams to improve annotation design, training, tooling, and quality controls.

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.

Design and optimize production-grade Databricks lakehouse architectures using medallion layers, Spark, Delta Lake, and Unity Catalog. Govern data and AI assets, implement cloud security, tune performance, optimize costs, and develop advanced SQL and Python or Scala solutions. Preferred experience includes GenAI, MLflow, CI/CD, streaming, orchestration, data warehousing, BI integration, and Databricks certifications.

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.

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.

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.

Design performance creatives, landing pages, lifecycle journeys, and conversion flows for acquisition across three Latin American markets. Use generative AI and automation tools to accelerate production, build scalable Figma systems, maintain brand consistency, and support creative testing. Partner with Paid Media to analyze performance metrics, develop hypotheses, and optimize assets through A/B testing. Scout emerging AI tools, document workflows, and manage multiple formats and languages in parallel.

The Freelance AI Artist will produce high-quality images and videos using AI technologies, collaborating with marketing to align with brand identity and experimenting with new workflows.

Join a global contributor network supporting flexible AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and verify cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Build and deploy production software for B2B fintech customers, owning features from design through monitoring and maintenance. Engineers may focus on backend-leaning product development or data and machine learning systems for risk, fraud, and spend intelligence. The role emphasizes AI-native development practices, strong software fundamentals, collaboration with Product and Design, ownership, and rapid learning in a multicultural environment.

Designs domain AI architecture and developer experience solutions. Responsibilities include software engineering, cloud and platform architecture on Azure, DevOps and DevSecOps, developer tooling, reusable patterns, architecture governance, documentation, enablement, and cross-functional collaboration. AI, generative AI, and multi-tenant SaaS experience are preferred. The role is remote and requires advanced English proficiency.

Build production LLM agents, multi-step workflows, MCP servers, evaluation and observability systems, and document-extraction pipelines. Architect AI-ready semantic data layers over Snowflake and dbt, develop Python ingestion and Airflow workloads, and implement retrieval, embeddings, governance, security, and reliable agent operations. Lead technical design, mentor peers, and advise clients in an embedded consulting engagement.