Director - Engineering

Key responsibilities

• Lead and scale the Core Recommendations & Surfaces team, owning critical systems that power retrieval, ranking, and core recommendation infrastructure for personalized experiences across the platform.
• Drive the technical strategy and roadmap for core recommendation platforms—optimizing relevance, exploration, and user engagement through scalable, low-latency, real-time systems.
• Architect backend services capable of serving hundreds of millions of users and handling massive concurrency spikes (e.g., 20x during live events) with sub-second latencies.
• Partner with Product, UX, and Data Science to define, build, and experiment with personalization enablers and surface-level improvements that impact discovery and engagement funnels.
• Elevate engineering standards by championing best practices in measuring model efficacy, observability, system resilience, latency optimization, cost efficiency, and experimentation velocity.
• Own and improve critical personalization metrics, such as engagement uplift, surface click-through rates, diversity ,coverage, and precision/recall of ranked items.
• Foster a high-performance culture centered around ownership, first-principles thinking, rapid iteration, and a strong focus on end-user outcomes.
• Hire, mentor, and grow a world-class engineering team, driving career development and delivering robust, high-quality, impactful systems.
• Create effective mechanisms to set goals for the team, create execution plans and track progress against those. You'll collaborate with other Developers, Program Managers, and tech support teams, in an agile environment to estimate and deliver objectives set together as a team.

Skills and attributes for success

• Experienced in managing multiple software engineering teams running core AI/ML services and/or ML systems at scale
• Previous experience with hands-on work and shipping products in an AI and/or ML domain, like recommender systems, NLP, information retrieval, relevance, ranking, or large language models.
• Strong track record previously as an individual contributor having engineered and shipped services & features at scale.
• Expertise in any of the programming languages (Python or Java or Golang)
• Hands-on architectural or distributed systems experience
• Experience with high scale databases - MySQL, NoSQL (Scylla, Cassandra, Redis, DynamoDB)
• Experience using any major cloud provider (AWS, Azure, or Google Cloud) for production applications
• Experience with CI/CD processes
• A strong track record of project delivery for large, cross-functional, projects and bringing in and growing engineering talent
• Excellent written and verbal communication skills with the ability to present complex technical information clearly and concisely to a variety of audiences

Preferred education and experience

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