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Sr Director - AI Delivery - 11891

Coupa makes margins multiply through its community-generated AI and industry-leading total spend management platform for businesses large and small. Coupa AI is informed by trillio

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Coupa Mexico City, Mexico City, Mexico Source published Sep 24, 2026 Verified 1 hour ago
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Overview

Coupa makes margins multiply through its community-generated AI and industry-leading total spend management platform for businesses large and small. Coupa AI is informed by trillio

Full job description

Coupa makes margins multiply through its community-generated AI and industry-leading total spend management platform for businesses large and small. Coupa AI is informed by trillions of dollars of direct and indirect spend data across a global network of 10M+ buyers and suppliers. We empower you with the ability to predict, prescribe, and automate smarter, more profitable business decisions to improve operating margins.

Why join Coupa? Pioneering Technology: At Coupa, we're at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend. Collaborative Culture: We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence. Global Impact: Join a company where your work has a global, measurable impact on our clients, the business, and each other. Learn more on Life at Coupa blog and hear from our employees about their experiences working at Coupa.

The Impact of a Senior Director, AI Delivery at Coupa:

The Senior Director, AI Delivery leads the engineering organization responsible for designing, building, deploying, and operating enterprise AI solutions across the company. This leader owns the end-to-end delivery lifecycle for AI initiatives, partnering closely with business stakeholders, AI Strategy, Enterprise Architecture, Data, Infrastructure, Security, and Product teams to transform business opportunities into production ready AI capabilities. The role is accountable for execution excellence, engineering quality, delivery predictability, operational stability, governance compliance, and business value realization across a portfolio of AI agents, automations, and intelligent workflows. The focus is on delivering enterprise grade AI products that are scalable, secure, measurable, and reusable.

AI Delivery Leadership Lead the enterprise AI Delivery Engineering organization. Build and scale a high-performing team of AI Engineers, AI Solution Architects and AI Operations Establish delivery standards, engineering practices, and operating models for AI solution development. Own execution across multiple concurrent AI programs and business domains. Enterprise AI Solution Delivery Lead delivery of enterprise AI solutions including: AI Agents Agentic Workflows AI-powered business automations Conversational AI Knowledge assistants Retrieval-Augmented Generation (RAG) solutions Multi-agent orchestration Ensure solutions are secure, scalable, maintainable, and reusable. Engineering Excellence Establish engineering standards for: Prompt engineering Agent development Tool integration MCP implementation API integrations AI workflow orchestration Code quality Reusable frameworks Secure development practices Drive adoption of reusable AI components and engineering accelerators. Delivery & Portfolio Management Own delivery execution across the AI portfolio including: Capacity planning Prioritization Roadmaps Resource allocation Milestone management Executive reporting Risk management Delivery metrics Ensure predictable execution across multiple AI initiatives. AI Operations (Run) Establish operational excellence for production AI systems by overseeing: Production monitoring Agent health Incident management Performance optimization Model performance Prompt optimization Cost optimization AI observability Drive continuous improvement after deployment. Governance & Responsible AI Create & Manage the AI Governance council, partnering with Security, and Compliance teams to ensure: Responsible AI practices Security reviews Privacy compliance Human-in-the-loop controls Auditability Model governance Risk assessments Regulatory compliance Ensure governance is embedded throughout the delivery lifecycle. Cross-functional Leadership Partner closely with: AI Strategy Enterprise Architecture Business Systems Data & Analytics Security Business Product Owners Legal Procurement Vendor Partners Align technology delivery with business priorities. Financial & Vendor Management Manage delivery budgets and strategic partners by: Overseeing vendor performance Managing delivery costs Driving AI platform optimization Tracking consumption and FinOps metrics Measuring ROI Optimizing engineering capacity Organizational Leadership Build a world-class AI delivery organization through: Talent development Workforce planning Coaching and mentoring Organizational design Hiring Performance management Engineering culture Innovation

12–15+ years of experience leading enterprise technology organizations. 7+ years managing engineering or enterprise application delivery / Data insights teams. Experience delivering AI, machine learning, or intelligent automation solutions at enterprise scale. Deep understanding of enterprise application ecosystems including CRM, ERP, HR, Finance, and collaboration platforms. Experience with LLMs, RAG architectures, agent frameworks, MCP, API integrations, orchestration frameworks, and enterprise AI platforms. Experience building and leading global engineering organizations. Strong executive communication and stakeholder management skills. Experience managing strategic vendors and systems integrators. Demonstrated success leading large transformation programs. Preferred Experience Experience with Google Gemini, Vertex AI, apigee, Anthropic Claude ecosystems. Experience integrating AI into enterprise platforms such as Salesforce, Netsuite, Zuora, or similar. Knowledge of Responsible AI, AI governance, and enterprise security. Experience implementing AI observability, AI testing, and operational monitoring frameworks. Familiarity with cloud-native architectures, DevOps, CI/CD, and modern software engineering practices.

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