Software Development Manager, Advertiser Growth - Global Optimization
Amazon
Description
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
Digital advertising represents a $400B+ global market, and Amazon's advertising business is one of the fastest-growing segments.
We are seeking an exceptional Software Development Manager to lead advertiser-facing initiatives that empower sellers to succeed with advertising across Amazon's global marketplaces. This is a high-impact leadership role at the intersection of artificial intelligence, large-scale distributed systems, and advertising technology, where you will drive the development of intelligent campaign structures, autonomous bidding systems, and sophisticated targeting capabilities that revolutionize how advertisers achieve their business objectives worldwide.
In this position, you will lead a team building next-generation advertising solutions that process billions of transactions daily across Amazon's tier-1 infrastructure. Your team's work directly impacts advertiser success by leveraging highly advanced techniques including predictive modeling, generative AI, agent-based reinforcement learning, and advanced optimization methods to create autonomous systems for bidding, targeting, and campaign management. This autonomous approach enables advertisers to focus on strategy while our systems handle the complex, real-time decisions that maximize their return on investment across diverse global marketplaces.
The technical challenges are substantial: you'll be architecting systems that must maintain low latency while processing massive scale, incorporating multiple ML models that learn and adapt continuously across different markets and languages, and ensuring rock-solid reliability for a mission-critical advertising platform. Your solutions must balance competing objectives—advertiser goals, marketplace dynamics, customer experience, and system constraints—all while operating autonomously with appropriate guardrails and explainability across global regions.
Beyond the technical complexity, this role offers the opportunity to shape the future of advertising at Amazon. As autonomous systems become increasingly sophisticated, your team's innovations will define how advertisers interact with Amazon Ads globally, potentially reducing manual campaign management from hours per week to minutes per month. You'll be building the foundation for truly autonomous advertising—systems that understand advertiser intent, adapt to market conditions across geographies, and deliver measurable business outcomes without constant human oversight.
Key job responsibilities
- Define long term vision and product strategy for Global Advertising for Sponsored Products and Sponsored Brands Advertisers
- Lead the end-to-end architecture, design, and implementation of brand new products and features for global advertising
- Drive technical decisions around predictive modeling approaches, generative AI integration, multi-agent reinforcement learning algorithms, control theory applications, and real-time optimization methods for autonomous bid adjustment
- Ensure system scalability, reliability, and performance for tier-1 production services handling mission-critical advertising workloads across multiple AWS regions
- Establish engineering best practices for ML operations (MLOps), including model training pipelines, A/B testing frameworks, continuous deployment, monitoring, and automated rollback mechanisms
- Design fault-tolerant systems with fallback strategies, and graceful degradation to maintain advertiser trust during system anomalies
- Balance technical debt with feature velocity, making strategic decisions about when to refactor versus when to iterate
- Build, mentor, and grow a high-performing team of software engineers and and applied scientists working on advanced autonomous systems and agentic AI