Top Artificial Intelligence Jobs in Mexico

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.

Design and build AI-first mobile apps using FlutterFlow: create user flows, wireframes, interactive prototypes, and production-ready builds. Integrate REST APIs, auth, state management, caching, and custom code; maintain reusable components and scalable design systems. Leverage AI tools across research, ideation, UI generation, testing, and documentation. Collaborate cross-functionally to iterate, optimize usability and accessibility, and deliver polished production-quality mobile experiences.

Lead pre-sales and delivery of OpenShift AI solutions: design and implement enterprise AI/ML platforms, drive MLOps adoption, architect training/serving/inference at scale, support Generative AI and LLM deployments, ensure governance, automation, and alignment with business and IT strategies.

Lead quality strategy for AI-enabled products by designing scalable automated test frameworks, validating AI-generated outputs and agentic workflows, integrating tests into CI/CD, defining quality metrics, identifying risks, and mentoring engineers to improve cross-team quality practices.

As an AI Engineer, you will develop and implement internal automation workflows, integrating various tools and APIs to improve productivity in design and development processes, primarily using LangChain and related frameworks.

The Lead AI Forward Engineer designs and delivers AI-powered solutions, guiding teams in automation, architecture design, and implementation. Responsibilities include system design, technology strategy, and cross-functional partnership to meet business needs effectively.

Lead and coordinate cross-functional value-creation and AI transformation initiatives: define measurable use cases, build KPI dashboards and business cases, track execution and benefits, support operating-model and SI transitions, and prepare executive-ready reporting to drive adoption and measurable business impact.

Provide technical support for NVIDIA Jetson embedded Linux platforms, perform board bring-up, JetPack/BSP integration, and hardware/software debugging. Deploy, optimize, benchmark, and troubleshoot AI inference and computer vision workloads using TensorRT, CUDA, DeepStream, ONNX Runtime, TensorFlow, and PyTorch. Collaborate with FAEs, customers, and sales, create documentation and demos, run trainings, and drive PoCs and design-in activity for edge AI solutions.

The Senior AI Engineer will develop AI-driven solutions using LLMs, focusing on prompt engineering, integration, research, and data utilization for payment systems.

Own and execute customers' AI roadmaps, aligning product capabilities to business strategies, ensuring successful adoption, driving revenue growth, and achieving high customer satisfaction through effective stakeholder engagement.

The AI Product Engineer will design and implement Agentic AI platforms for Financial Services, engaging directly with clients to define use cases and leading the full SDLC for deployment.

Lead design and evolution of a large-scale distributed backend platform. Build and optimize microservices, APIs, and event-driven data workflows on cloud infrastructure. Drive architectural decisions, ensure scalability, availability, security, and observability; integrate AI/ML capabilities; mentor engineers; and lead incident response and continuous platform improvements.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

Work on Applied AI platforms and features: design, build, and ship AI-powered full-stack systems (backend, APIs, data, frontend). Integrate embeddings, agentic systems, and automation into products and workflows, participate in production support, and collaborate with cross-functional teams under senior guidance.

The Sr. AI Engineer will design, develop, and deploy scalable ML models, collaborate on AI-driven features, and mentor team members while optimizing machine learning infrastructure.

Lead identification, design, deployment, and measurement of AI-powered automations across operations. Map high-friction workflows, build agent- or rule-based automations, create Metabase dashboards, partner with Product/Engineering to instrument data, and document solutions for handoff.

The AI Sales Intelligence Analyst will develop AI-powered analytics for sales, collaborating with cross-functional teams. Responsibilities include building conversational agents, integrating data systems, and ensuring data quality and governance.