Senior Product Manager, AI Experimentation Platform

CSC Generation • Cottonwood Heights, UT

2d • Hybrid

About The Position

Backcountry is transitioning from manual, low-volume A/B testing to an always-learning agentic experimentation platform that designs, launches, monitors, and optimizes experiments across its ecommerce sites. The Senior Product Manager will own the platform from the ground up, including its vision, roadmap, prioritization, and decisions about where AI agents can act autonomously and where human oversight is needed. The role is accountable for measurable improvements in conversion and revenue.

The position carries end-to-end responsibility on a lean team. Success within six to twelve months means delivering a working platform that runs trusted experiments across multiple sites, increasing testing velocity without compromising statistical rigor, and producing revenue and conversion improvements traceable to platform-run experiments. The role reports to the Vice President of Product and UX and is based in Cottonwood Heights, Utah, with a hybrid schedule requiring three days per week in the office.

Requirements

• At least 5 years of product management experience, including ownership of a platform, data, or internal tooling product.
• Hands-on experience running or building A/B testing and experimentation programs at scale in ecommerce or other high-traffic digital products.
• Strong statistical grounding in experiment design, including power and sample-size calculation, significance, peeking, multiple comparisons, and guardrail metrics.
• Hands-on experience building with AI and LLMs, including agentic workflows, prompt design, tool integrations, and evaluating AI output quality.
• Working knowledge of experimentation infrastructure, including feature flagging, randomization, event tracking, and warehouse-native metrics.
• Strong analytical skills and hands-on use of SQL, GA4, BigQuery, Looker, or similar tools.
• Demonstrated measurable impact on conversion, revenue, or testing speed.
• Excellent communication skills and ability to influence engineering, data, and business stakeholders.
• Must provide a valid LinkedIn profile URL in the application, or a credible reason for not having one and alternative evidence of professional background to verify identity.
• Employment is contingent on a background check, including verification of prior employment dates.
• Must be willing and able to attend a mandatory in-person interview before an offer.

Nice To Haves

• Experience with experimentation platforms such as Optimizely, Statsig, Eppo, GrowthBook, LaunchDarkly, or an in-house equivalent.
• Experience with adaptive experimentation, including multi-armed or contextual bandits, Bayesian methods, or variance-reduction techniques such as CUPED.
• Experience testing AI- or ML-driven experiences such as search, recommendations, or personalization.
• Experience running experimentation across multiple brands or storefronts on a shared platform.
• Background in outdoor, specialty, or multi-brand ecommerce.

Responsibilities

• Own the vision, roadmap, and prioritization for the agentic experimentation platform, including decisions about what to build or buy.
• Define how AI agents participate throughout the experiment lifecycle, from hypothesis generation and variant creation to test setup, QA, live monitoring, and ship-or-rollback decisions.
• Establish safeguards for autonomous testing, including statistical standards, sample ratio mismatch and anomaly checks, revenue and margin thresholds, approval workflows, and automatic rollback.
• Build adaptive optimization using multi-armed and contextual bandits so traffic can shift toward winning experiences while tests are running.
• Partner with engineering and data science on experimentation infrastructure, including assignment and bucketing, feature flags, event tracking, the metrics layer, and a statistics engine built on GA4 and BigQuery.
• Define and instrument platform success metrics, including test velocity, win rate, revenue impact, and result trustworthiness.
• Make experimentation self-serve for merchandising, marketing, UX, and engineering teams so they can launch and interpret tests without a specialist.
• Create standards and playbooks for metric definitions, test design, and readouts to ensure consistent, comparable, trusted results across sites.
• Partner with engineering, design, analytics, merchandising, and marketing to turn business goals into a shipped platform and a culture of testing.

Benefits

• Paid time off policies.
• 401(k) match.
• Medical, dental, and vision coverage.
• A variety of supplemental policies.
• Employee discounts across the company's portfolio of brands.
• Outdoor perks and recognition and wellbeing programs are described as part of the company culture.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed