AI, Automation & Tech Lead

Role Overview

The LATAM AI, Automation & Tech Lead is responsible for driving the technical strategy, architecture, adoption, and end-to-end implementation of AI-powered solutions and automation initiatives across the Buenos Aires operation and the broader LATAM region.

This role represents a dual leadership capability: combining deep hands-on technical expertise and software architecture with operational vision and cross-functional leadership leveraging WPP's resources and platforms. The Lead will identify opportunities for process optimization, design robust and scalable technical architectures, lead the development of automated workflows and tools, and ensure that all technical implementations adhere to enterprise-grade engineering and security standards.

Working closely with Project Management, Design, Development, QA, and operational leaders, the Lead will translate complex operational challenges into reliable, automated, and scalable software solutions, while fostering a culture of innovation, technical excellence, and continuous improvement.

Key Responsibilities

1. AI & Automation Strategy & Technical Roadmap

• Identify opportunities to leverage AI, machine learning, and automation to optimize workflows and increase production capacity across the entire region.
• Define and execute the technical roadmap for AI and automation, aligning business priorities with technical feasibility, maintainability, and scalability.
• Continuously evaluate emerging technologies, AI Agents, LLM frameworks, and APIs to determine practical, secure applications across the organization.

2. Technical Leadership, Architecture & Governance (Tech Lead Focus)

• Act as the ultimate technical authority for all automation, scripting, and AI implementations within the LATAM operation.
• Define the technical architecture, technology stack, and engineering standards for internal tools, scripts, APIs, and automated pipelines.
• Establish best practices for code quality, version control (Git), CI/CD pipelines, automated testing, error handling, and comprehensive technical documentation.
• Ensure all solutions comply with global technology, data privacy, and information security standards (including API key management, data governance, and intellectual property protection).
• Conduct architecture and code reviews, ensuring solutions are robust, reusable, modular, and maintainable.

3. Hands-On Solution Design & Development

• Lead and actively participate in the hands-on architecture, prototyping, and development of complex automations, custom scripts, integrations, and AI agent-based workflows.
• Develop and deploy custom AI solutions leveraging modern LLM orchestration frameworks, system architectures, and API-based integrations.

4. Operational Efficiency & Process Optimization

• Analyze end-to-end production workflows across Design, Development, Project Management, and QA to pinpoint inefficiencies and manual friction.
• Partner with other functional leads to quantify operational pain points and prioritize high-ROI automation initiatives.
• Standardize and document modular workflows that can be replicated across different accounts and projects.
• Directly impact production KPIs: turnaround times (cycle times), error rates, delivery volume, and operational costs.

5. AI Adoption, Enablement & Technical Mentorship

• Act as a technical mentor for developers, technical PMs, and contributors, elevating the overall technical capabilities of the team.
• Promote the practical, effective, and responsible use of WPP-provided AI tools across all disciplines.
• Organize training sessions, workshops, and technical documentation to drive self-serve automation and widespread tool adoption.

6. Cross-Functional Leadership & Discipline Ownership

• Act as the regional benchmark and owner of the AI, Automation & Technology discipline.
• Coordinate with local, regional, and global technology and innovation teams to align local developments with global WPP platforms, avoiding duplication of efforts.
• Clearly communicate technical concepts, progress, roadmaps, and ROI metrics to both business leaders and non-technical audiences.

7. Performance Measurement, Reliability & Continuous Improvement

• Define and monitor metrics for system reliability, performance, and automation uptime, alongside business metrics (time saved, productivity gains).
• Establish a continuous improvement lifecycle: gathering user feedback, refining prompts/models, refactoring code, and decommissioning obsolete scripts.
• Provide visibility into automation ROI, demonstrating tangible impact on production targets and operational capacity.

Success Measures

Success in this role will be measured by the ability to:

• Achieve Operational Automation Targets: Lead technical execution toward operational milestones (e.g., 60% of total delivery automated by 2026; 80% target by 2027).
• Technical Robustness & Reliability: High availability (uptime), maintainable codebases, zero security/data breaches, and reusable technical components across accounts.
• Measurable ROI: Demonstrated time savings, reduced turnaround times, and lower production error rates.
• Adoption & Cultural Impact: Measurable increase in daily active usage of AI tools and automated pipelines across Design, PM, Dev, and QA.
• Discipline Maturation: Establish modular repositories, clear documentation, and solid technical governance for all automations developed in Buenos Aires and the region.

Key Qualifications & Technical Skills

• Technical Background: Bachelor’s degree in Computer Science, Software Engineering, Systems Engineering, or equivalent practical experience.
• Programming & Scripting: Strong hands-on experience in modern languages used for automation and AI integration (e.g., Python, TypeScript/JavaScript, Node.js).
• AI & LLM Ecosystem: Hands-on experience working with OpenAI/Anthropic APIs, prompt engineering, agentic frameworks (LangChain, LlamaIndex, or custom agents), and vector/embedding workflows.
• APIs & Integrations: Extensive experience consuming and building RESTful APIs, webhooks, and integrations with third-party tools (Figma API, Jira API, Slack, cloud storage buckets, etc.).
• Automation Platforms: Familiarity with orchestration/low-code platforms (Make, n8n, Power Automate, Zapier), as well as custom code-based orchestrators.
• DevOps & Standards: Experience with Git workflows, CI/CD, cloud environments (AWS/GCP/Azure), containerization (Docker), and automated testing.
• Leadership & Communication: Proven ability to translate business requirements into technical architecture and communicate seamlessly with both technical and non-technical stakeholders.