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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 Thinking – Understands how data, models, optimization, and workflows connect end to end
Data-Driven – Uses experimentation and rigorous measurement to prove value
Influence & Communication – Aligns executives, field leaders, and engineers without direct authority
Change Leadership – Builds trust in AI with frontline users; earns adoption rather than mandating it
Qualifications
Qualifications:
5+ years leading technology implementations, data-driven decision tools, or product management, with a proven track record of delivering results An execution leader fluent in technology: a working understanding of data and core AI/ML concepts sufficient to partner credibly with data scientists and engineers Track record owning a business case and measuring realized value after launch Comfortable with KPI design, baselines, and test-and-learn measurement (e.g., pilots, A/B tests) Experience in field service, logistics, home services, or other multi-site operational businesses strongly preferred Experience leading adoption and change management for new tools or processes with frontline or operational teams Proven cross-functional leadership with operations, finance, marketing, IT, and external implementation partners Familiarity with Microsoft Fabric, Azure, Power BI, field service management platforms, or similar a plus Exposure to generative or agentic AI tools and AI governance a plus Comfortable working in Agile, PMO-led, or hybrid environments Bachelor’s degree in business, engineering, computer science, or a related field, or equivalent experience leading technology implementations
Additional Requirements:
Ability to lead multiple concurrent, high-visibility programs in a fast-paced environment
Executive presence; effective communication across technical and non-technical audiences, from front-line employees to the C-suite
Strong organization, attention to detail, and follow-through
Ability to travel as needed (approximately 1–2 times per quarter)
