Social Triage Specialist, Muse​/Online Operations - Support Specialist IV

Social Triage Specialist, Muse/Online Operations - Support Specialist IV

4+ months

Remote (Once offices reopen, will be required to be onsite.)

Open to other Client locations -- Hybrid/Onsite in MPK/SEA/NYC once offices reopen

Monitor social platforms, primarily X, for mentions of Muse at very low latency; classify each mention against the Muse triage rubric; and personally own the middle bucket: posts that warrant a response but do not warrant executive engagement. Engage the user publicly or by DM, resolve the issue, and close the loop.

• Monitor inbound Muse mentions on a continuous sweep cadence (queue polled roughly every 2 minutes) and apply a first-pass tier within the 30-minute live-pass latency target.
• Classify every post against the Tier 1 / 2 / 3 rubric using the live-pass dimensions only: account context (follower count, historical engagement, verified outlet or credentialed journalist, known amplifier) and content (misinformation, claim severity, exec tagged or named, specific product issue, repro present). Make the escape-or-not call with high precision. Immediately route hard-override cases (misinformation, damaging press claim, exec tagged or named) to the Tier 1 queue for comms and on-call.
  
  Log Tier 3 posts to the signal store with no outreach.
• Own Tier 2 end to end. Respond to the user on-platform, ask the clarifying questions needed to establish a repro (prompt, settings, model, steps, screenshots), and drive the thread to a stated resolution. Extract and log the repro, assign an issue category, file or link the corresponding bug, and track it to closure so the user gets a real answer rather than an acknowledgement.
• Record tier, , and  on every item so misclassifications are auditable, and flag posts that are below threshold but trending for continued re-scoring.
• Draft and reuse approved response language for recurring Muse issues; elevate to comms when a situation needs net-new external language rather than improvising it.
• Hand off cleanly on shift change with a live queue state, including open threads, pending repros, and anything held for the maturity pass.
• Surface recurring themes from Tier 2 and Tier 3 volume to product and comms partners on a regular cadence.
• Minimum viable Muse product expertise (developed in ramp)
• Working fluency in Muse's surfaces, generation flows, model behavior, and known limitations, sufficient to tell a real defect from expected behavior, a user error, or a feature request.
• Familiarity with current known issues, shipped fixes, and public positioning, so the responder does not confirm something already resolved or speculate on anything unannounced.
• Ability to judge whether a complaint is concrete enough that an engineer could act on it, which is the actual Tier 2 bar.

• Experience responding to users in public social channels on behalf of a brand or product, with a track record of de-escalating rather than inflaming.
• Demonstrated judgment under time pressure and incomplete information, with a bias toward escalating ambiguous reputational risk rather than absorbing it.
• Strong, concise written voice that holds up in public reply threads.
• Comfort with technical product detail: can read a stack of screenshots and prompt settings and turn it into a usable repro.
• Ability to work a shift-based schedule, including evenings and weekends, to sustain continuous low-latency coverage.
• Rigorous logging discipline. Every call is recorded with the rule that fired it.

• Experience responding to users in public social channels on behalf of a brand or product, with a track record of de-escalating rather than inflaming.
• Strong, concise written voice that holds up in public reply threads.
• Comfort with technical product detail: can read a stack of screenshots and prompt settings and turn it into a usable repro.

• Prior work in a trust and safety, community, social care, or incident-adjacent triage function.
• Prior exposure to generative AI image or video products and the common failure modes users report.
• Familiarity with social listening and queue tooling.

• Prior work in a trust and safety, community, social care, or incident-adjacent triage function.
• Prior exposure to generative AI image or video products and the common failure modes users report.