Senior Manager, AI Product
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公司名称 ARS-Rescue Rooter 概述 地点:远程 加入American Residential Services,我们是全美最大的住宅HVAC、管道和电气服务提供商之一,拥有7,000名团队成员和超过50年的经验。我们在24个州拥有70多个分支机构,横跨东西海岸,正在持续增长并招聘专业人员,以支持我们的分支办公室、现场施工、……
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职位描述 · 原文
Company Name ARS-Rescue Rooter Overview Location: Remote Join American Residential Services , one of the nation’s largest providers of residential HVAC, plumbing, and electrical services with 7,000 team members and more than 50 years of experience. With 70+ locations in 24 states, coast-to-coast, we are growing and hiring professionals to help support our branch offices, field trades, call centers, and corporate office. The Senior Manager, AI Product leads some of ARS’s flagship AI-first products. These enterprise-scale initiatives apply machine learning, AI, and AI agents to how we serve our customers and drive profitable growth across the enterprise. This role reports to the VP, Data Applied Intelligence (D AI) and owns the measurable business outcomes of each flagship program, from strategy and business case through production adoption and value realization. You’ll serve as: Product lead for D AI’s flagship AI products, beginning with AI-driven dispatch optimization for field service Outcome owner accountable for driving, measuring, and reporting the realized business value of each flagship Strategic partner to business leaders across operations, call center, marketing, finance, and IT who are partners in execution This role works cross-functionally with data engineering, data science, platform, business teams, and external implementation partners to turn complex operational problems into AI products that people trust, adopt, and that deliver measurable financial impact. Responsibilities Own product strategy, roadmap, and business case for a portfolio of flagship AI products, aligned to ARS’s enterprise transformation initiatives such as dispatch, call center, pricing and discounting, membership, marketing and conversion, and fleet and capital efficiency Define product vision, release plans, and success criteria for each flagship Translate operational problems into product requirements, success metrics, and acceptance criteria that data science and engineering teams can build against Arbitrate scope, sequencing, and trade-offs with operations, branch, finance, and IT; manage intake, backlog, releases, and dependencies across concurrent programs Own value measurement for each flagship: baselines, KPI definitions, experiment design (A/B tests and branch-level pilots), and attribution of benefit to the right business lever Lead pilot design, launch readiness, and scaled rollout, planning field-facing releases around seasonal peak-demand periods Own adoption and change management for each product including training, communication, and feedback loops with the business users it serves Guide decisions on where AI acts on its own and where people stay in the loop, weighing risk, accuracy, customer impact, and value Manage implementation partners and vendors; support build-vs-buy evaluations, statements of work, and renewals Ensure responsible AI: explainable recommendations, human override, model monitoring, and data governance, privacy, and compliance requirements are met Communicate progress, value, and risk to executive leadership in clear, business-first terms Build the AI Product function over time — practices, templates, and team — as the portfolio grows Success Measures: Flagship products delivered on the committed roadmap, with clear visibility into priorities, status, and risk Measured, auditable business value (revenue, margin, and cost) attributed to each flagship against an agreed baseline Strong adoption and sustained use across the business operations and functions each product serves Business owners and executive sponsors aligned on scope, sequencing, and success criteria A repeatable AI product playbook (discover, pilot, scale, measure) applied across flagships Core Competencies: Strategic Vision – Connects a multi-year AI roadmap to near-term, value-producing releases Accountability – Owns business outcomes, not just delivery Business Acumen – Ties product decisions to revenue, margin, and cost levers Systems Think
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