Engineering Manager - Search (Consumer, Global Discovery)

We are on the lookout for an Engineering Manager to lead one of our squads within the Search Domain. This squad builds and owns some of the core services that power search and discovery. 

These are low-latency services handling tens of thousands of queries per second across multiple markets. They must remain fast, and continuously improve in relevance. Your squad will own the full lifecycle of these services: design, build, operate, and iterate.

In this role, you will guide a team of engineers, own the quality and operational health of your services, and partner closely with Product and Data Science to deliver measurable improvements to the search experience.

Lead & Grow a High-Performing Squad

• Own team health, engagement, and inclusion, ensuring every engineer has growth opportunities and clear career paths.

• Develop engineers through regular 1:1s, structured feedback, clear expectations, and performance management.

• Hire and onboard talent with strong backend and search infrastructure skills, while contributing to domain-wide recruiting efforts.

Own Technical and Delivery Outcomes

• Experience delivering Conversational Search or LLM-powered search interfaces.

• Lead your team in delivering high-quality, maintainable services in a Java 

• Drive Agentic Engineering adoption and a transformation towards fully Agentic SDLC.

• Ensure reliable sprint execution, proactive risk management, and transparent stakeholder communication. Manage cross-squad dependencies.

Drive Operational Excellence

• Maintain the reliability of services through robust monitoring, alerting, and incident response. 

• Ensure on-call readiness, runbooks, and blameless post-mortems are part of the squad's culture.

• Continuously improve delivery and operational health: cycle time, deployment frequency, safe reindexing rollouts, and relevance regression detection.

Partner with Product & Data Science to Deliver Impact

• Translate product discovery goals and relevance targets into actionable engineering work with clear priorities.

• Collaborate with Data Science on experiments and A/B tests to measure relevance improvements (MRR, NDCG, click-through rates).

• Keep the squad aligned with business objectives and user value—ensuring improvements translate into measurable customer impact.