Amazon Advertising is investing heavily in building AI agent infrastructure that's transforming how millions of advertisers make strategic decisions. We're responsible for defining and delivering the next generation of real-time data platforms that power over 30 advertising agents and skills across Amazon's ecosystem. Our products are strategically important to Amazon's advertising business, processing billions of data points daily. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing rapidly with a wide range of new opportunities.

The Ads Real-Time Data Service team is solving one of the most critical challenges in advertising AI: instant access to advertiser context. We're building the infrastructure that provides immediate, pre-computed access to advertiser data via Model Context Protocol (MCP) servers—an emerging standard for AI agent-data interaction. We're building summarized data for context using a mix of state of the art techniques like CodeAct and RAG-based embeddings, achieving a fundamental transformation in how AI agents interact with data.

As a Software Development Manager for this team, you'll lead the engineers building the horizontal platform that enables all 30+ advertising agents and skills to move at speed. You'll own the strategic direction for real-time data ingestion from sources like our data warehouse and Kafka streams, the data processing pipelines that generate pre-computed advertiser context, and the MCP server infrastructure that delivers this data with sub-second latency. This role offers a unique blend of technical leadership and strategic influence, with ownership over a platform that's becoming the automatic choice for every agent team at Amazon Advertising.

You'll collaborate with Applied Scientists pioneering advanced AI patterns, work with engineering teams across advertising agents and skills, and partner with product leaders to define the future of agent-data interaction. Your expertise will be instrumental in establishing architectural patterns for real-time data delivery at scale, optimizing for both performance and developer experience, and building a platform that makes trustworthy, instant advertiser context the default for all agents.

Key job responsibilities
Technical Leadership & Platform Vision
- Lead the design and evolution of platform architecture, establishing patterns for real-time data ingestion, processing, and delivery that scale across advertising agents and skills
- Partner with Principal Engineers and architects across Amazon Advertising to influence long-term technical direction for agent infrastructure
- Own the technical roadmap balancing immediate customer needs with platform scalability and extensibility

Team Management & Development
- Manage, mentor, and grow a team of engineers building mission-critical real-time data infrastructure
- Foster a culture of innovation, technical excellence, and customer obsession while maintaining sustainable engineering practices
- Conduct performance reviews, career development planning, and succession planning for team members
- Create quality bar raisers within the organization and promote technical leaders

Platform Operations & Excellence
- Establish operational excellence standards for a platform processing billions of data points with 1-3 minute refresh cadences
- Drive system reliability, monitoring, and incident response practices ensuring 99.9%+ availability for agent teams
- Implement delivery and quality governance mechanisms ensuring timely execution of platform roadmap
- Define success metrics and key performance indicators demonstrating measurable impact on agent performance, developer productivity, and customer experience

Cross-Functional Collaboration & Influence
- Collaborate with agent builder teams to understand data requirements and drive platform adoption
- Partner with Applied Scientists to productionize research innovations in agent orchestration and large language model optimization
- Engage with product managers and senior leadership to align platform capabilities with business strategy
- Work with Technical Program Managers to coordinate cross-team dependencies and ensure successful launches

A day in the life

Morning: AI-Assisted Spec Development and Architecture
Your day starts reviewing system metrics showing 2.3 billion data points processed overnight with 47-second average latency. You join a design review where your team is presenting a technical specification for the new advertiser context framework—generated using Kiro, our coding agent. The spec outlines how agent teams can onboard new datasets in under one day through schema-driven configuration. You review the AI-generated spec, challenge assumptions about error handling, and suggest refinements. The team makes adjustments and you approve the design, which will move to implementation today.

Mid-Morning: Strategic Planning and Communication
You're crafting a document for your Director outlining the quarterly roadmap: expanding from 11 to 20+ advertiser data types, onboarding 5 new advertising agents and skills, and achieving 99.95% availability. You articulate how the platform is becoming the automatic choice for agent teams, reducing their engineering overhead from 15+ weeks to days while delivering near-perfect response success rates.

Afternoon: Rapid Development Cycles and Team Growth
After lunch, you facilitate a sprint planning session where your team commits to delivering real-time Kafka stream integration for campaign updates. One of your engineers shares a technical specification generated by Kiro this morning for a new caching layer that could reduce token consumption by another 40%. You review the spec together, discuss the approach, and approve it. The engineer will use Kiro to generate the implementation this afternoon—spec to code in a single day.

You spend time mentoring your tech lead on system design principles for distributed data processing. They're using Kiro to generate specifications for MCP server optimizations and you provide feedback on the prompts and validation criteria. Later, you meet with your manager to discuss resource capacity planning—you need to hire 3 more engineers to support the growing demand from advertising agents and skills.

Late Afternoon: Incident Response and Stakeholder Management
An incident occurs: one of the data ingestion pipelines from our data warehouse is experiencing delays. You join the war room, coordinate with the upstream team, and guide your engineers through the mitigation. You document lessons learned and schedule a post-mortem. Before end of day, you respond to a message from an advertising agent team asking about data availability for their use case—you connect them with your tech lead and add their requirements to the backlog.

About the team
The Ads Real-Time Data Service team is a highly motivated, collaborative and fun-loving group of engineers building the foundational platform for Amazon's advertising AI future. We are entrepreneurial and have a bias for action with a broad mandate to experiment and innovate. Our team operates at the intersection of real-time data engineering, AI agent infrastructure, and distributed systems engineering—solving problems that directly impact how millions of advertisers interact with Amazon's advertising products.

We value technical excellence, customer obsession, and sustainable engineering practices. Our team includes engineers with diverse backgrounds in distributed systems, real-time data processing, AI/ML infrastructure, and platform engineering. We celebrate innovation (patent submissions encouraged), knowledge sharing (weekly tech talks), and continuous learning. We maintain a sustainable pace with minimal on-call burden, flexible work arrangements, and a strong focus on work-life balance. We're at the forefront of AI-assisted development, using tools like Kiro to accelerate our development cycles from weeks to days.