GenAI Architect - 11096

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 GenAI Architect at Coupa:

We are seeking an experienced GenAI Architect to lead the design and strategic direction of our enterprise AI solutions leveraging Google Cloud's AI ecosystem. This role is a core part of our AI Delivery leadership team, responsible for architecting scalable, production-ready AI systems using Google ADK (Agent Developer Kit), Vertex AI, and related Google Cloud services that drive organizational transformation and measurable business value.

This position combines deep architectural expertise with strategic leadership, ensuring that our AI solutions are designed for scale, security, and long-term sustainability. The GenAI Architect will guide technical teams, establish architectural standards, and partner with executive stakeholders to translate business vision into robust, enterprise-grade GenAI Architectures within the Google Cloud environment.

What You'll Do:

• Enterprise GenAI Architecture: Design and define the architectural vision for multi-agent AI systems using Google ADK, Vertex AI Agent Builder, and GCP services, ensuring solutions scale across the enterprise and align with business objectives.
• Platform Strategy & Standards: Establish architectural standards, design patterns, and best practices for AI development on Google Cloud Platform, including model deployment strategies, agent orchestration patterns, and integration frameworks.
• Vertex AI Platform Design: Architect comprehensive AI platforms leveraging Vertex AI capabilities including model training pipelines, fine-tuning strategies, vector search architectures, model governance, and production monitoring frameworks.
• Cloud Integration Architecture: Design sophisticated integrations between AI agents and enterprise systems using Google Cloud services including BigQuery, Cloud Functions, Cloud Run, Pub/Sub, Dataflow, and third-party enterprise applications (Salesforce, SAP, etc.).
• Technical Leadership & Mentorship: Provide technical guidance and architectural oversight to AI developers, cloud engineers, and cross-functional teams. Review designs, conduct architecture reviews, and mentor team members on best practices.
• Responsible AI Framework: Define and implement enterprise-wide responsible AI frameworks using Vertex AI's governance tools, including bias detection, model explainability, compliance monitoring, privacy controls, and ethical AI guidelines.
• Scalability & Performance: Design for scale, reliability, and cost-optimization across AI workloads. Define strategies for model serving, caching, load balancing, and resource optimization on GCP infrastructure.
• Innovation & Evaluation: Research and evaluate emerging AI technologies, Google Cloud AI capabilities, and industry trends. Recommend adoption of new tools, frameworks, and architectural patterns to maintain competitive advantage.
• Stakeholder Engagement: Partner with executive leadership, business stakeholders, and technical teams to understand strategic priorities and translate them into actionable architectural roadmaps and technical strategies.

• Proven experience (10+ years) in software architecture, cloud architecture, or AI/ML architecture with at least 3-5 years focused on production AI systems.
• Demonstrated expertise designing and implementing enterprise-scale AI solutions on Google Cloud Platform with deep knowledge of Vertex GenAI Architecture and capabilities.
• Strong architectural knowledge of AI/ML systems, agentic AI patterns (ReAct, planning, multi-agent orchestration, tool use), and experience architecting solutions with Google ADK or Vertex AI Agent Builder.
• Expert-level understanding of Google Cloud Platform architecture including Vertex AI, BigQuery, Cloud Functions, Cloud Run, GKE, Pub/Sub, and enterprise integration patterns.
• Deep knowledge of MLOps architecture, including Vertex AI Pipelines, model versioning, A/B testing strategies, model monitoring, and CI/CD for ML systems.
• Proven track record of architecting and delivering multiple AI/ML solutions into production that created significant business impact.
• Strong proficiency in Python and architectural understanding of AI/ML frameworks including Google ADK, Vertex AI SDK, TensorFlow/JAX, and agent orchestration frameworks.
• Exceptional ability to communicate complex architectural concepts to executive leadership, technical teams, and non-technical stakeholders through documentation, diagrams, and presentations.
• Bachelor's degree in Computer Science, Data Science, or a related field; Master's degree or equivalent advanced experience preferred.
Preferred :
• Experience architecting solutions with Vertex AI advanced features including vector search (Matching Engine), custom training at scale, distributed training, and multi-modal AI systems.
• Deep expertise with Gemini API, embeddings architectures, and retrieval-augmented generation (RAG) patterns including hybrid search, reranking, and grounding strategies.
• Experience with enterprise architecture frameworks (TOGAF, Zachman) and cloud architecture certifications (Google Cloud Professional Cloud Architect, Professional ML Engineer).
• Hands-on experience architecting security and compliance frameworks for AI systems, including Google Cloud security best practices, IAM, VPC Service Controls, and data governance.
• Proven experience implementing responsible AI governance frameworks using Vertex AI Explainable AI, Model Monitoring, fairness metrics, and bias mitigation strategies at scale.
• Experience architecting real-time AI systems with low-latency requirements, streaming architectures, and event-driven patterns.
• Background in enterprise data architecture, data mesh patterns, or knowledge graph architectures integrated with AI systems.
• Published thought leadership, speaking engagements, or contributions to the AI/ML architecture community.