Responsibilities

• Develop and own audience strategy for enterprise technical stakeholders, including CIOs, CTOs, information security, architects, and developers
• Create technical content including demos, architecture overviews, whitepapers, security documentation, and competitive proof points
• Build programs that support technical evaluation, including developer enablement, sandbox and POC frameworks, and self-serve onboarding paths
• Craft narratives that explain Meta's AI platforms, models, and APIs credibly to technical audiences and to executive decision makers
• Partner with product and engineering to translate platform capabilities into market-facing value, and to feed audience insight back into the roadmap
• Guide and partner with cross-functional teams, both global and regional, in developing sales collateral and technical marketing content
• Conduct market and competitive research on enterprise AI platforms to identify positioning gaps and opportunities

Requirements

• BA/BS degree
• 8+ years of experience in product marketing, product management, or technical sales/marketing
• Technical fluency sufficient to speak credibly with developers about APIs, integrations, and platform architecture
• Experience marketing or managing API-first products, developer platforms, AI/ML products, or comparable enterprise technology
• Demonstrated understanding of how enterprise technical stakeholders find, evaluate, and implement technology solutions
• Track record of collaborating with cross-functional/cross-org teams to drive results
• Experience simplifying complex technical concepts and communicating effectively with different audiences (e.g. product, engineering, sales, executives, customers)
• Experience contributing at both strategic and tactical levels
• Project and program management skills

Preferred

• Familiarity with enterprise AI governance, compliance requirements, and procurement processes
• Engineering, computer science, or technical background
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience with AI agent platforms, LLMs, or conversational AI products
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience building developer enablement programs, POC frameworks, or technical documentation strategy
• Data analytics skills
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies