Project Manager, AI
Description
• Own the full lifecycle of 2–3 concurrent AI implementations for Fortune-100 P&C insurers, moving each engagement from discovery kickoff through UAT, production cut-over, and post-go-live optimization in an average of 8–12 weeks.
• Translate complex insurance workflows—claims indexing, underwriting triage, FNOL ingestion—into crisp technical requirements that our cross-functional squad (Business Analyst, Solution Architect, Automation Engineer) can execute against with zero ambiguity.
• Build and maintain a living project plan in Jira/Asana that tracks every sprint, dependency, risk, and deliverable; update it daily so that internal leadership and customer executives see the same single source of truth.
• Run weekly steering-committee calls with carrier VPs and directors, presenting live dashboards that tie automation KPIs (STP %, accuracy, FTE savings) directly to hard-dollar ROI and SLA improvements versus legacy manual processes.
• Proactively surface scope creep, timeline slippage, or data-quality issues within 24 hours of detection; negotiate trade-offs with customer stakeholders while protecting the integrity of the delivery schedule.
• Shepherd user-acceptance testing by designing test scripts, coordinating business-user feedback, and driving defect triage so that production readiness gates are passed on the first attempt.
• After go-live, monitor model drift and throughput for 30 days, partnering with our Data Science team to fine-tune InsurGPT prompts and extraction rules until the customer’s success criteria are exceeded.
• Document every lesson learned in Confluence playbooks that the next Project Manager can lift-and-shift, compounding the velocity of our entire Customer Success organization.
• Champion change-management best practices—training materials, comms plans, and executive readouts—so that end-users adopt the new AI workflows enthusiastically rather than reluctantly.
• Contribute to product roadmap discussions by feeding real-world customer pain points back to Engineering, ensuring that the platform evolves faster than the market’s expectations.
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