About this role
This role will help drive global go-to-market strategy and execution for Meta's enterprise AI products, including agent platforms, models, and APIs. Aligned to enterprise technical audiences, this role lives at the intersection of technical marketing, product, sales and client enablement.
You will be responsible for understanding technical stakeholders across the buying committee, from CIOs and CTOs who make decisions to the developers and architects who run proofs of concept, and for knowing how each of them finds, evaluates, and implements AI solutions. You will help build Meta's point of view on enterprise AI and use that POV to shape our go-to-market approach and product roadmap.
Technical fluency is a requirement. You must be able to hold a credible conversation with a developer about APIs, integration patterns, and model behavior, and then turn around and make the governance and business case to a CIO. You will be expected to have or rapidly develop working knowledge of market-leading AI platforms, model capabilities, and integration protocols.
Cross-functional leadership, executive communications skills, ability to manage multiple concurrent projects, and comfort with ambiguity are musts. You will be expected to develop knowledge of how large enterprises evaluate and adopt AI, including build versus buy dynamics, AI governance and procurement processes, and the technical criteria that determine whether a platform clears evaluation.
Direct experience with API-first products, developer platforms, or enterprise AI is preferred. The ideal candidate will also have a strong existing point of view on enterprise AI adoption and a track record of shipping technical content and programs, not just strategy.
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
Qualifications
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 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