Staff AI Cost Management Architect

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Team

Join FinOps Governance team that is part of the Global Cloud Services organization.

You'll apply your cloud architecture and FinOps expertise to design solutions that bring financial accountability and intelligent optimization to our AI and cloud investments. Working alongside cloud engineers, data scientists, AI platform teams, and Finance leadership, you'll architect the systems and strategies that enable AI cost visibility, optimization, and governance at scale.

About the role

We're looking for a Staff FinOps AI Cost Management Architect to design the technical vision and reference architectures for AI cost management at ServiceNow. This is a strategic role focused on designing solutions, defining standards, and partnering with stakeholders to drive financial optimization across our AI platform. You'll architect semantic data models for AI billing attribution, design integration patterns for AI agents to safely access FinOps data (including Model Context Protocol), and establish frameworks for cost optimization, forecasting, and financial governance. As a trusted technical advisor, you'll present to Engineering, Finance, and executive stakeholders, translating business requirements into scalable architectural solutions that enable millions in cost savings.

What you get to do in this role:

• Design reference architectures for AI cost management platform, including data ingestion, semantic modeling, analytics layers, and AI agent integration patterns.
• Define architectural standards for AI-to-FinOps data interactions using protocols like Model Context Protocol (MCP), ensuring security, governance, and safe autonomous workflows.
• Architect semantic data models and consumption layers for AI billing that enable multi-dimensional cost attribution (by model, token, GPU, team, project, customer).
• Create architecture blueprints for real-time cost visibility, anomaly detection, forecasting, and optimization across AI workloads on AWS, Azure, and GCP.
• Partner with Engineering and AI Platform teams to embed cost KPIs into architecture reviews and ensure alignment with enterprise architecture standards.
• Present architecture proposals, trade-off analyses, and strategic recommendations to technical and executive stakeholders across Finance, Engineering, and Product teams.
• Create technical documentation, architecture diagrams, decision records, and playbooks that enable platform engineers to implement FinOps solutions.
• Act as a trusted technical advisor to leadership on AI cost management strategy, capacity planning, and cloud financial optimization.

Qualifications

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
• 8+ years of experience in cloud architecture, solutions architecture, or enterprise architecture roles with proven track record designing complex cloud solutions with a Bachelor’s degree in Computer Science, Engineering or related technical field; or 6 years and a Master’s degree; or a PhD with 3 years’ experience; or equivalent experience.
• Deep expertise in multi-cloud architecture (AWS, Azure, GCP) with strong understanding of cloud billing models, pricing structures, and FinOps principles.
• Experience architecting data platforms, analytics solutions, or data products including semantic layer design and data modeling methodologies.
• Understanding of AI/ML platform architecture including LLM services (Bedrock, Azure OpenAI, Vertex AI), model inference patterns, GPU compute, and AI cost economics.
• Expert ability to create architecture diagrams, technical documentation, and communicate complex technical concepts to both technical and executive audiences.
• Demonstrated experience presenting to and influencing senior technical and business leaders, with strong stakeholder management and collaboration skills.
• Strong analytical and problem-solving abil