APAC Business Development - Monetization Partnerships
Drive long-term revenue growth and strategic value by leading three core workstreams: (1) negotiating and executing strategic bespoke deals with high-value partners (e.g., AI enablers, marketplace/commerce platforms, agentic partners, creator platforms, data providers), (2) shaping early-stage product initiatives where the business model, value exchange, and commercial terms are not yet defined, and (3) developing new ecosystems that unlock net-new revenue opportunities across APAC markets.
Responsibilities- Lead complex, multi-stakeholder negotiations
- Influence product strategy through partner feedback loops
- Drive outcomes across a portfolio spanning APAC and global markets
- Serve as the connective tissue between Meta's product roadmap and the region's most consequential commercial partnerships
- Accelerate Meta's ability to meet businesses where they are by building the partner integrations, deal structures, and go-to-market frameworks that turn product capabilities into scaled revenue
- 8+ years experience in business development, partnerships or product roles
- Demonstrable understanding of how technology works, including practical experience with Meta's 0 to 1 product launches
- Experience in gathering requirements across broad areas and partners, and converting and developing them into a large scale solution
- Proven experience in working successfully with cross-functional peers and stakeholders, both internally and externally
- Ability to operate with a high degree of autonomy displaying leadership, organizational and execution skills with a sense of urgency
- Experience in analyzing and making decisions based on data, and using these findings to close partnerships
- Experience in working with legal, product, and engineering functions
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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