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 general, measurable impact on our clients, the business, and each other.

Learn more onLife at Coupa blog and hear from our employees about their experiences working at Coupa.

The Impact of an AI Engineer at Coupa:
We are seeking a hands-on Agentic AI Developer / AI Engineer to design, build, test and deploy agentic AI solutions leveraging Google Cloud's AI ecosystem. This role is a core part of our AI Delivery "Build" team, responsible for translating business challenges into production-ready AI agents and solutions using Google ADK (Agent Developer Kit), Vertex AI, and related Google Cloud services that create measurable business value.
This position combines deep technical expertise with practical execution on Google's AI platform, ensuring that our agentic AI solutions are well-designed, robustly built, and successfully deployed. The Agentic AI Developer will partner closely with business stakeholders, QA Specialists, and Cloud Engineers to build, test,



and scale responsible AI solutions from concept to production within the Google Cloud environment.
In a forward deployed role, You will embed directly with the portfolio teams whose problems you are solving, work in their tools and their meetings, and deliver agentic and automation solutions in the flow of work: inside the systems people already use every day, not as one more application they have to learn.
What You'll Do

Design & Build with Google ADK:Design, develop, test, and deploy autonomous and semi-autonomous AI agents using Google ADK, Vertex AI Agent Builder, and agentic patterns to address key business challenges.
Vertex AI Implementation:Leverage Vertex AI capabilities including model training, fine-tuning, vector search, and orchestration to build production-grade AI solutions that integrate seamlessly with enterprise systems.
End-to-End Development:Own the end-to-end technical lifecycle of AI projects on Google Cloud Platform, from initial proof-of-concept and prototyping through to production deployment using Vertex AI Pipelines, monitoring with Vertex AI Model Monitoring, and continuous iteration.
Google Cloud Integration:Build integrations between AI agents and Google Cloud services including Gemini Enterprise, Cloud Functions, Cloud Run, Pub/Sub, and enterprise data sources to enable intelligent automation across the organization.




Cross-Functional Collaboration:Partner with business stakeholders to understand requirements and collaborate closely with QA Specialists and Cloud Engineers to ensure solutions are reliable, scalable, and seamlessly integrated within GCP infrastructure.
Responsible AI Implementation:Implement, test, and monitor safeguards for AI agents using Vertex AI's responsible AI tools to mitigate risks, including bias detection, model explainability, compliance monitoring, and operational limits. Ensure solutions are fair, explainable, and robust.
Agentic Architecture with ADK:Contribute to the architecture and selection of frameworks, tools, and orchestration logic using Google ADK and Vertex AI to build, manage, and scale multi-agent systems effectively.
Prototype Fast, in the Open:Ship a working prototype in days, not quarters. Put it in a real user's hands early, watch them use it, and iterate on what you observe instead of what was requested.
Build MCP Servers and Tool Integrations:Design, build, and maintain Model Context Protocol (MCP) servers, connectors, and tool layers that give Claude, Gemini, and other models safe, governed, audited access to Coupa business systems and data.
Stay Multi-Model and Pragmatic:Choose the right model, framework, and pattern for each job across Claude, Gemini, and open models. Make cost, latency, and accuracy tradeoffs deliberately instead of defaulting to one vendor.
Know When It Isn't an Agent:Recognize when workflow automation, a scheduled job, a cleaner integration, or simply deleting a step is the faster, cheaper, more durable fix. Reach for the smallest tool that solves the problem.
Instrument and Prove Impact:Measure every deployment. Track usage, cycle-time reduction,

📌 Ai Engineer (Xico)
🏢 Coupa
📍 Xico