Engineering Manager, AI Search

Responsibilities

• Build and manage a diverse and inclusive team of engineers working on search ranking, query understanding, and search UX.
• Recruit, coach, and develop engineers; ensure regular feedback and progress on goals.
• Collaborate with cross-functional peers to set team direction and improve search quality.
• Facilitate planning, prioritization, sequencing, and staffing of work.
• Maintain high-quality bar for reliability, latency, and relevance metrics.
• Drive project execution using data and experimentation to improve search quality.
• Shape engineering organization practices, recruiting, onboarding, planning, and prioritization.

Requirements

• Experience managing engineering teams on search, ranking, relevance, or related areas.
• Deep understanding of building high-quality search at scale (millions of pages, sub-3-second queries).
• Background in search quality, ranking algorithms, and experimentation methodologies.
• Passion for mission-critical infrastructure, including bug fixes and reliability.
• Excitement about AI-powered search: embedding models, hybrid lexical-semantic search, LLMs, connector search, multimodal search.
• Ability to create collaborative, empowering team environments.
• Empathetic and direct communication for feedback and alignment.
• High tolerance for ambiguity and change.
• Passion for line management and team culture.

Nice-to-Haves

• Experience with AI connectors, enterprise search, or multi-data source search.
• Experience building RAG-based features or LLM integration in search.
• Managed teams for experimentation and A/B testing frameworks.
• Managed teams at startups during rapid growth.
• Experience rolling out engineering and management practices (code review, performance reviews, levels and ladders).

Compensation

Estimated base salary range for San Francisco and New York: $280,000 - $330,000 per year, plus equity and benefits.