Director of Engineering, Business Messaging Optimization

Meta•Menlo Park, CA

20d•$271,000 - $347,000

About The Position

Meta's Business Messaging team helps businesses engage customers through messaging on WhatsApp, Messenger, and other surfaces. Marketing Messages Optimization owns the end-to-end delivery funnel for marketing messages, including signals, ranking, auctions, pricing, and delivery infrastructure. The organization determines which message reaches which person, when it is delivered, how often, and at what price, balancing business value with a high-quality experience for people. The Director of Engineering will lead a multi-team organization of engineering managers and senior engineers, set multi-year technical strategy, and work closely with Ads, Business Agent, WhatsApp, data science, product, privacy, and other Meta teams. The role combines large-scale ads ranking and auction systems with messaging-specific constraints, including a limited opted-in audience, privacy commitments, and high user-experience standards. It is a high-impact, revenue-critical role at the intersection of monetization and messaging.

Requirements

10+ years of technical industry experience in software engineering.
7+ years of engineering management experience, including managing other engineering managers.
Demonstrated experience delivering large-scale impact using machine learning and partnering with cross-functional teams.
Track record of building and scaling engineering organizations across multiple teams or product areas.
Experience establishing engineering strategy and roadmaps spanning multiple teams and cross-functional partners.
Experience diagnosing and resolving complex organizational health challenges, including retention, team structure, and leadership development.

Nice To Haves

Experience driving measurable revenue impact through machine learning and infrastructure investments, validated through rigorous online experimentation.
Experience operating revenue-critical systems during peak traffic and spend periods.
Experience with notifications, messaging, or other supply-constrained surfaces where frequency, timing, and user fatigue matter.
Experience with large-scale candidate retrieval and serving systems, including capacity and efficiency tradeoffs.
Experience with auction mechanism design, reserve pricing, bidding and pacing, or quality and integrity modeling in ads systems.
Advanced degree in Computer Science, Machine Learning, Economics, or a related field.
Experience building machine learning systems under privacy constraints or limited signal availability.
Experience leading organizations that build large-scale ads ranking, auction, pricing, or ads delivery systems.
Experience setting technical direction across organizational boundaries, with key dependencies owned by partner teams.

Responsibilities

Lead and grow a multi-team engineering organization spanning delivery infrastructure, ranking and auction, and signals and experimentation; hire and develop engineering managers and senior technical leaders.
Set the multi-year technical vision and roadmap for marketing message delivery, including candidate retrieval, ranking, quality modeling, auction design, and pricing.
Drive a quality-aware auction that balances advertiser value, business outcomes, and the experience of people receiving messages.
Scale serving infrastructure for rapid traffic growth across multiple products while improving efficiency, reliability, and observability.
Build the signals and measurement foundation for optimization in a privacy-constrained environment, including experiments that distinguish the effects of pricing, quality, and supply.
Manage the delivery funnel as one system, making tradeoffs across infrastructure capacity, model quality, and auction policy to maximize long-term value.
Set a high operational bar for revenue-critical systems, including on-call health, alerting, and safe launch practices during peak seasons.
Build partnerships with Ads ranking and delivery, WhatsApp, data science, product management, and privacy and policy teams to align roadmaps and deliver cross-organizational initiatives.
Partner with product leadership to ensure the optimization platform supports multiple products and buying surfaces.