Top Artificial Intelligence Jobs in Mexico City

As a Senior Software Engineer, you will develop core data pipeline components for an AI-native data warehouse, oversee feature delivery, and ensure data quality and reliability.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

As a Staff Software Engineer at Juniper Square, you'll lead architectural decisions and develop AI-powered systems, mentoring engineers and ensuring high-quality technical standards while collaborating with cross-functional teams.

As a Customer Support Expert, you will respond to customer inquiries via social media and email, providing excellent service on behalf of various brands.

Lead AI validation strategy for LLMs, RAG, and agent systems. Build automated CI/CD-integrated evaluation pipelines, design semantic and prompt regression tests, implement guardrails and confidence scoring, monitor production AI quality, and define metrics/KPIs in partnership with engineering and governance teams.

Design and build scalable Node.js backend services and AI-powered integrations. Implement LLM API integrations, RAG, vector DBs, AI orchestration, message-queue-driven architectures, CI/CD pipelines, and collaborate on architecture, testing, and reliability.

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.

Early-career operations role executing Salesforce system enhancements, resolving process issues, building reports/dashboards, implementing Flows and minor Apex updates, and applying AI tools to improve post-sales CX workflows.

Support Central Operations by evaluating, implementing, and maintaining AI agents and low/no-code automations (e.g., Zapier). Build unified dashboards to track AI agent performance, reduce manual work, document automations, run LLM evaluation/monitoring, train stakeholders, and provide feedback to align AI with business workflows.

Support Central Operations by evaluating, implementing, and maintaining AI-driven automations and low-code tooling (e.g., Zapier). Build unified dashboards to track AI agent performance, drive internal adoption, document automations, run LLM evaluation/monitoring for human-in-the-loop workflows, and collaborate with product, engineering, and ops to reduce manual work and improve reporting.

Design and supervise technical architectures for intelligent agents and LLMs, implement MCP and A2A multi-agent flows, integrate vector stores and RAG, collaborate with MLOps for continuous deployment, memory and context management, and work with product, UX, data, and backend teams to align solutions with business needs.

As a Lead Software Engineer at PMG, you will design, develop, and deploy scalable AI-driven solutions, mentor other engineers, and enhance the Alli platform for digital marketing. Responsibilities include coding, code reviews, and integration with cross-functional teams.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Design, build, and deploy generative AI solutions and agentic workflows using LLMs. Implement RAG architectures with vector databases, integrate AI services with enterprise systems, deploy AI workloads on AWS, and ensure monitoring, governance, and security for production AI applications.

Lead backlog ownership for complex, multi-team AI-centered engagements. Translate product strategy into epics and stories, drive ambiguity resolution, facilitate refinement and Agile ceremonies, mentor other POs, partner with UX, and champion AI-forward backlog and documentation practices to ensure delivery quality and clear client communication.

As a GTM Engineer / AI Engineer, you'll architect and scale systems for growth, develop AI workflows, and unify tools like Salesforce and HubSpot to enhance the customer lifecycle.

Lead design and implementation of a scalable, secure multi-tenant SaaS using .NET and Angular. Own full-stack delivery from domain modeling through frontend, automated testing, CI/CD, and production support while mentoring engineers and leveraging AI-assisted development to accelerate quality delivery.

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.

The AI Strategy Consultant will drive marketing strategy using AI, work with teams to implement solutions, and enhance customer outcomes.

The role involves rapid prototyping and architecting production LLM pipelines for AI in marketing workflows. Responsibilities include developing proofs of concept, making AI architecture decisions, building production data agents, and understanding user workflows for seamless AI experiences.

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.

The AI Full Stack Developer will design and build AI applications using modern technologies, developing prototypes and production-ready systems while collaborating with various teams to leverage AI capabilities and enhance performance.

Design and deploy LLM-based integrations and agentic workflows across the GTM tech stack to boost pipeline, accelerate deal velocity, and reduce vendor spend. Build predictive models and Next-Best-Action recommendations, ensure data integrity in Salesforce, and train GTM teams on AI tooling and prompt/agent management to improve sales, marketing, and customer success outcomes.

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.