Finance Manager, Frontier AI Assets

Amazon is hiring a highly effective Finance Manager to partner with the Frontier AI Assets (FAI) team in leading our Human-in-the-Loop (HITL) Data Annotation Network. In this role, you are the strategic financial business partner to our AI Data Operations and Engineering leaders working to deliver a comprehensive portfolio of high-value, trusted AI assets, enabling frontier model capabilities for Amazon businesses and external customers. These assets are developed in-house (1P) and sourced from a curated network of third-party (3P) partners for certification of downstream model impact as part of the collection process. In this high-impact role, you will establish financial frameworks, own full P&L oversight and financial modeling for complex unit economics across our global operations network of specialized domain experts (coding, STEM, legal, reasoning), and drive capital allocation efficiency across our data annotation supply chain. If you are looking for a role to apply your financial acumen to deliver insights and drive high-velocity decision making to help shape how AI models perform real-world actions, learn from human feedback, and drive results with key performance indicators that balance quality, speed, cost and impact then this role is for you! A successful candidate will love to learn and be curious and dive deep to understand and identify business trends, analyze quantitatively, problem-solve and prioritize. Strong oral and written communication skills are crucial, as well as the ability to work autonomously with a proven work ethic and track record of delivering results. Key job responsibilities • Financial Ownership & Strategic FP&A: Drive end-to-end financial forecasting, annual planning, and monthly variance analysis for our global HITL operations network. • Unit Economics & Cost Modeling: Develop dynamic cost models analyzing cost-per-unit and cost-per-hour across varied worker tiers, skill complexities, and technical domains. • Cross-Functional Business Partnership: Partner directly with AI Operations and Engineering teams to align data procurement budgets with model training schedules and capacity planning. • Vendor & Network Optimization: Evaluate and identify spend optimization opportunities across the global network to optimize cost, throughput, and output quality. • Governance & Controls: Implement scalable operational tracking and cost controls to ensure budget accuracy as operations scale.