Position Overview

Burn Boot Camp is one of the fastest-growing fitness franchises in the country - 400+ Gyms, a fiercely loyal Member base, and an aggressive growth path to 1,000 locations by 2028. Franchise Partners operate independent businesses within our national brand. What they have never had - until now - is enterprise-grade intelligence delivered daily: a clear signal on what to prioritize, what is at risk, and what is working. Building that intelligence layer is the mandate behind this role.

We are looking for a Head of AI to own that layer end-to-end. This is not a research role. It is a builder's role - someone who can architect AI systems that reach every Franchise Partner daily, lead a modern data platform, and translate strategy into shipped product. You will sit inside the Technology organization, report to the VP of Technology, and operate at the intersection of data engineering, applied AI, and franchise operations.

We are making foundational platform decisions right now. The person we hire will shape the architecture, own the roadmap, and build the team that carries it forward.

Responsibilities

AI Strategy & Product Roadmap

• Define and drive Burn's enterprise AI strategy - from Franchise Partner intelligence to operational automation to generative AI applications.
• Own the AI product roadmap across multiple active workstreams, sequencing priorities against business impact and technical readiness.
• Lead architecture decisions: data pipelines, model serving, LLM integration, API design, and the feedback loops that make AI outputs better over time.
• Partner directly with operations, marketing, franchise development, and finance to identify where AI creates the most leverage.

Franchise Partner Intelligence

• Architect and deliver AI-powered tools that surface actionable daily intelligence for 300-1,000 Franchise Partners - identifying what to prioritize, what is at risk, and what is driving performance.
• Own the end-to-end product experience: data ingestion, scoring models, AI-generated recommendations, and the quality and confidence layer that ensures reliability at scale.
• Develop performance frameworks that translate raw data into decision-ready insights - reducing dependence on manual analysis and field support escalations.
• Define and track Franchise Partner adoption as a first-class success metric alongside accuracy and uptime.

AI Workstreams & Applied Products

You will lead multiple simultaneous AI initiatives across the business. Active workstreams include:

• Franchise Partner daily intelligence and performance analytics platform
• Generative AI for internal and Member-facing applications
• AI-powered lead nurture and CRM enrichment
• Intelligent automation for finance, operations, and service workflows
• Conversational AI and agent-based tooling for internal teams

Data Platform Leadership

The AI strategy runs on the data platform - and you'll own both. You'll own the strategy and lead the team that executes it, including architecture, governance, and roadmap for:

• Snowflake - our enterprise data warehouse. You'll own the platform strategy, data modeling standards, cost governance, virtual warehouse design, and the roadmap for expanding Snowflake as our single source of truth across all data sources.
• Operational Data Store (ODS) - the integration and transformation layer connecting source systems (membership, POS, CRM, franchise ops) to analytics and AI. You'll define the architecture that keeps data clean, current, and trustworthy.
• Domo - Burn's primary BI platform for home office reporting, franchise development dashboards, and executive analytics. You'll own the roadmap for what Domo solves, what Snowflake serves directly, and how the two layers complement each other.
• End-to-end data governance: field-level definitions, data dictionaries, freshness SLAs, quality monitoring, and the access controls that protect 300+ Gyms' business data.

Team & Vendor Leadership

• Build and lead the Data & AI team - hiring, developing, and retaining engineers and analysts who build in production. You'll inherit a team and have the mandate and budget to grow it as the roadmap scales.
• Manage key vendor and implementation partner relationships, including the technology partner responsible for platform delivery.
• Set engineering standards: code quality, testing, documentation, security, and deployment practices across all AI and data systems.
• Represent AI and data at the Technology Advisory Committee and in cross-functional leadership forums.

Qualifications

Required

• 7+ years in data engineering, ML engineering, or AI product roles - with a track record of shipping AI systems in production at scale.
• Hands-on experience with cloud data warehouse platforms - Snowflake strongly preferred.
• Deep fluency in modern data stack: ELT/ETL design, data modeling, API integration patterns, and real-time vs. batch pipeline trade-offs.
• Experience designing and deploying LLM-based or generative AI products - prompt engineering, retrieval-augmented generation, output quality and safety.
• Strong product instincts: ability to translate complex, ambiguous business problems into well-scoped AI solutions with clear success criteria.
• Demonstrated ability to lead cross-functional initiatives and manage vendor/partner relationships.

Strongly Preferred

• Background in franchise, multi-location retail, fitness, or hospitality - with working knowledge of unit-level economics and how operators make day-to-day business decisions.
• Experience designing data products for operationally focused, non-technical end users - where simplicity, trust, and adoption are as important as analytical depth.
• Familiarity with Domo, HubSpot, Loopspark, or similar franchise, CRM, and membership technology ecosystems.
• Track record of building high-performing teams and developing talent, not solely inheriting established organizations.

This position description is not intended to be and should not be construed as an all-inclusive list of responsibilities, skills or working conditions associated with this position. While this description is intended to accurately reflect the position's activities and requirements, management reserves the right to modify, add or remove duties as necessary.