Top Artificial Intelligence Jobs in Mexico City

Lead the definition and governance of enterprise AI architecture; design and oversee LLM-powered systems, RAG pipelines, agentic frameworks, and inference infrastructure; advise executives on AI strategy and risk; create reusable AI reference architectures and CoE artifacts; mentor engineers and integrate AI into DevOps/QA practices while ensuring regulatory and security compliance.

The Sr. AI Engineer will design and implement scalable machine learning models, optimize ML operations, and mentor team members while collaborating across departments to enhance AI-driven features.

Design, build, and deploy bespoke AI/LLM-driven solutions on the Salesforce platform. Handle end-to-end delivery including data modeling, integration, agent orchestration, debugging, prototyping, and client-facing implementation and optimization.

Develop and maintain MCP tools and the MCP Toolbox for Databases; expand test coverage for agentic coding assistants; refactor and maintain test frameworks; convert technical posts into production-ready sample code and documentation; build real-world data applications (QueryData) to support product R&D and collaborate with cross-functional teams to accelerate agentic AI adoption.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.

Lead company-wide AI use case lifecycle from intake to production: assess workflows, scope solutions, run pilots, govern vendor/tool stack, measure business impact, and report outcomes to leadership.

The Data Growth Associate will drive global data collection strategies, user acquisition, and operational optimization while collaborating with cross-functional teams.

The QA Automation Engineer will enhance testing processes, collaborate with teams to build automated frameworks, and support modern software delivery in a cloud-native environment.

Lead design and evolution of scalable, secure cloud-native SaaS platforms using C#/.NET. Define architecture standards, champion microservices, DDD, CQRS, event-driven and API-first approaches, mentor engineers, improve performance, observability, and security, and integrate AI-assisted development tools and workflows across teams.

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.

Lead Product Engineer will develop AI-driven accounting software, focusing on backend services using Python, while also contributing to the frontend with React and Next.js. They will mentor team members and drive project success from ideation to release.

Lead design and implementation of scalable, secure Python-based distributed systems and AI/LLM agentic workflows. Own features from design through production, remediate technical debt, ensure testability, security (SCA), observability, and collaborate with product and engineering leadership.

As a Sr. Fullstack Engineer, you will design and develop scalable applications using C# and .NET for backend and React for frontend, while integrating AI technologies.

Build and maintain Python/FastAPI backend services and APIs, implement React frontend components, integrate MongoDB and AWS, collaborate via GitHub, participate in agile sprint planning, and work with AI and product teams to improve scalability and reliability.

Perform outbound prospecting (cold calls, email, LinkedIn) to identify and qualify B2B AI SaaS leads, book discovery calls and demos, maintain CRM records, collaborate with marketing and sales, hit monthly KPIs, and stay current on AI/SaaS trends.

Lead design, build, and scale client-facing and internal automation systems. Create advanced workflows (GoHighLevel, n8n/Make/Zapier), integrate platforms via APIs/webhooks, document SOPs, advise clients, maintain CRMs and troubleshoot live systems for reliability and scalability.

Outbound-focused SDR role selling AI SaaS: prospect via calls, email, and LinkedIn; qualify leads, engage decision-makers, book demos for AEs; maintain CRM records and meet monthly KPIs while collaborating with marketing and sales.

Design, build, and optimize GoHighLevel automations and AI-driven workflows across client accounts. Rigorously test automations, document SOPs, manage multiple projects, collaborate with teams and clients, and improve systems for scalability, efficiency, and performance.

Design, develop, and deploy AI-powered automation systems using Claude Code and n8n. Build scalable workflows and pipelines, prototype with the CTO, troubleshoot and optimize automations, document processes, and work directly with clients to gather requirements and recommend solutions that improve operational efficiency.

Drive end-to-end high-ticket sales in AI and automation: prospect, conduct discovery calls, nurture leads, manage pipeline in CRM, and close deals. Execute high-volume outbound campaigns using cold calling, email, and LinkedIn while meeting revenue targets and refining outreach with leadership.

Design, build, and scale AI-driven automation and CRM systems using GoHighLevel and tools like n8n/Make/Zapier. Integrate platforms via APIs and webhooks, create multi-step workflows for lead gen, sales, and operations, maintain internal infrastructure, troubleshoot deployments, and produce SOPs and client-facing documentation.

Manage and deploy AI-driven automation and workflows, onboard clients, translate requirements into actionable automations, design prompts for LLMs, troubleshoot and iterate systems, coordinate with AI engineers, and track project timelines and performance.

Design, develop, and deploy scalable AI/ML solutions using LLMs and generative AI. Build RAG systems, chatbots, automation workflows, and production model pipelines; collaborate with product and engineering teams, monitor and improve model performance, and document systems.

Design, build, and deploy AI-powered automation workflows using LLM APIs and workflow tools (n8n, Zapier, Go High Level). Integrate APIs/webhooks, debug and optimize workflows, and evolve internal scalable AI infrastructure. Collaborate with operations to gather requirements and iterate, while researching new AI tools and improving system reliability.

Design, build, and maintain AI-driven automations and lightweight internal tools using Make.com, LLMs, APIs, and basic code. Integrate platform data (Shopify, Google Ads, Meta, Looker Studio), document systems, train staff, and research emerging AI tools to boost team efficiency and scale operations.