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Fireworks is a Series D AI infrastructure platform ($17.5B valuation) backed by NVIDIA, Sequoia, and others, enabling companies to build and serve specialized AI models. The Social and Community Manager role is a hands-on, execution-heavy position focused on narrative building, trend judgment, and community engagement in the fast-moving AI infrastructure space.
You'll track real-time conversations across social platforms, Discord, and community channels to identify high-impact moments worth amplifying. The role requires sharp judgment on what narratives deserve Fireworks' voice and the ability to move quickly with strong instincts for tone and timing. You'll create on-brand, data-informed content that makes technical AI topics shareable and drive engagement across social channels.
Key responsibilities include monitoring social and community platforms daily using analytics tools, tracking metrics like engagement, reach, sentiment, and community health, then translating insights into actionable content recommendations. You'll own the social calendar, generate fresh content formats, and ship consistently while maintaining creative edge. Community engagement is central—moderating discussions, answering questions, fostering helpful conversations, and supporting community programs like ambassador initiatives, newsletters, AMAs, and cohorts.
You'll also help plan and execute virtual and in-person events, webinars, and meetups, measuring impact to improve future initiatives. Cross-team collaboration is essential: you'll maintain organized calendars, trackers, and dashboards while sharing data-driven insights with marketing, product, and engineering teams.
Must-haves include 5-8 years of hands-on social or community management experience (developer or AI communities preferred), sharp judgment on trend relevance, strong analytics and reporting skills, self-starter mindset, creative thinking, hands-on community growth experience (Discord, Reddit, X, forums), proficiency with social analytics tools, meticulous organization, daily use of LLMs and generative AI tools, and strong execution in fast-paced environments. Nice-to-haves include community program experience, familiarity with AI infrastructure or open-source model ecosystems like Hugging Face, basic video/multimedia skills, and startup background.
