Staff Software Engineer, Ads Manager Platform

What you’ll do

• Design, build and ship end-to-end features and platform improvements in Ads Manager, with a front-end–leaning full-stack focus across React/TypeScript and backend services.
• Lead modernization work in key surfaces (for example, Create Flow and Reporting) by moving legacy code to modern React patterns, GraphQL/Relay and shared validation and state-management frameworks.
• Improve Ads Manager stability and developer velocity by strengthening tests, hardening deploy pipelines and tightening monitoring and alerting for critical advertiser flows.
• Partner with product and platform teams across Ads Manager and core infrastructure to define platform patterns and land cross-team changes safely and incrementally.
• Use AI assistants to accelerate coding, refactors and test creation for migrations and feature work, while applying your own judgement to review, adapt and validate all AI-generated changes.
• Use AI to synthesize logs, metrics, incidents and experiment data into clear, actionable insights that inform design decisions, rollout plans and post-incident improvements.
• Document patterns, reference implementations and runbooks so other Ads teams can self-serve on the Ads Manager platform, and keep these resources current as the stack evolves.

What we’re looking for

• 8+ years of experience building and shipping production full-stack applications, including significant time working with modern React and TypeScript on large, multi-team codebases.
• Deep experience in at least one backend stack and in typed APIs (REST or GraphQL), including designing data contracts, handling migrations and operating services in production.
• Experience modernizing legacy web code (for example, class components and Redux) into hooks, context and shared abstractions, with a focus on readability, reuse and testability.
• Strong track record improving reliability and velocity for critical user-facing surfaces through observability, automated testing (unit, integration and E2E) and safer deploy patterns.
• Demonstrated ability to use AI to improve speed and quality in your workflow (for example, generating drafts for code, tests or docs), along with clear strategies for validating and correcting AI-assisted work.
• High integrity and ownership in how you use AI: you protect sensitive data, avoid over-reliance on AI outputs and stay accountable for the final design, code and system behavior.
• Effective cross-functional partner who can collaborate with Product, Design and other engineering teams, communicate tradeoffs clearly and move work forward in an ambiguous, evolving platform environment.
• Bachelor’s degree in Computer Science, a related field or equivalent experience.