Director, Enterprise AI Enablement

iFIT is creating a new Director, Enterprise AI Enablement role to lead the company's shift toward AI-powered ways of working. This is a high-visibility, high-impact role that sits at the intersection of technology, enablement, and enterprise strategy.

Reporting to the VP of Information Technology, you will shape iFIT's strategy for AI tooling and governance, co-chairing the established cross-functional AI Governance Committee and setting the guardrails that keep AI use responsible and compliant. You will also help set the technical standards and patterns business teams build on, so AI use cases across the company are consistent and able to scale.

With those guardrails and patterns in place, the heart of the role is transforming how iFIT runs, from manual, human-driven workflows to intelligent, AI-powered operations. You will lead a community of business AI leaders across the operational functions, training, coaching, and equipping them to put AI to work in their own areas. As a force multiplier, your job is to lift the whole company, helping teams build and sustain this work on their own and keep improving as they grow more capable. This mission keeps you hands-on. As a player/coach, you will work with each function to find automation opportunities and build alongside teams to speed results. That proximity keeps you close to the business, strengthening relationships and your grasp of how the work really flows, so you always know what will help most and where iFIT should invest next.

This role is ideal for a proven AI and automation leader who pairs technical depth with business fluency, able to spot where automation will pay off across the business, and build it, while raising AI capability across the whole company.

COMMITMENTS

• Stand up the community of business AI leaders across the priority functions, with the roster, cadence, and working relationships to drive adoption and automation from within each team.
• Establish the foundation for responsible AI: the guardrails, technical standards, and the framework for evaluating and monitoring agents so they can be trusted in production.
• Identify the highest-value automation opportunities across the business and deliver early, tangible wins, including automating business processes that span multiple areas of the company.
• Build the operating rhythm that sustains momentum: a working feedback loop, adoption and impact metrics, and a prioritized roadmap leadership can act on.

RESPONSIBILITIES

Set Strategy, Standards & Governance

• Shape iFIT's strategy for AI tooling and governance, deciding which platforms and tools the company standardizes on and where to focus first for the biggest operational gain.
• Help set the technical standards, architecture, and patterns business teams build on, so AI use across the company is consistent, sound, and able to scale.
• Monitor the fast-moving AI market and continually assess emerging tools and techniques, so iFIT invests early in what will matter and keeps its edge.
• Co-chair the cross-functional AI Governance Committee, alongside a Legal and an IT infrastructure lead, setting the guardrails and approved-tool standards that keep AI use responsible and compliant.

Activate AI Across the Business

• Build and lead a community of business AI leaders across the operational functions, Finance, HR, Supply Chain, Marketing, Product, and beyond, coaching and equipping them to put AI to work inside their own areas.
• Make sure every function gets the training it needs to use AI well, whether you deliver it directly, bring in outside expertise, or equip teams with materials they can share themselves.
• Enable these teams to build and sustain AI-powered work within and across their own functions, growing what the whole company can do.
• Help teams redesign how the work actually gets done around AI, moving from manual, human-driven workflows to AI-powered ways of working.
• Spread what works from one team to the next, turning wins in one function into repeatable practice across the company.

Build Hands-On as a Player/Coach

• Work closely with teams to understand how their work flows, and advise on where AI and automation can help, whether or not you are the one who builds it.
• Roll up your sleeves and build alongside teams, taking a defined need and delivering the tools, automations, or templates to meet it, then handing them off for the teams to own and run.
• Integrate AI agents and automations into existing enterprise systems (ERP, CRM, HRIS, and the like), working alongside IT Engineering to keep solutions sound and stable.
• Keep improving what is already live: harden the automations teams depend on and refine them as needs change.

Measure and Improve

• Track the impact of AI across the business, from efficiency and error reduction to adoption and output by team, and report it to the VP, IT and executive leadership.
• Monitor the agents and automations deployed across the company, tracking performance and output quality, watching for behavior that goes off track, and ensuring responsible use and data security.
• Turn what you learn working alongside the business into program improvements, refining the tools, training, and guardrails, and flagging the new AI capabilities iFIT should invest in or pursue next.

QUALIFICATIONS

Required

• You are an experienced, AI-forward software engineer with 6+ years in a senior or lead capacity.
• You have delivered products, integrations, and automations that produced measurable business benefits. You build sustainably, documenting how things work and training others to run and maintain them, so what you hand off keeps working without you.
• Strong working fluency with agentic AI systems: you understand how agent loops, tool use, RAG, and multi-agent workflows fit together, and you can build and integrate them with enterprise data and systems.
• You understand why evaluating an agent for accuracy, reliability, and safety matters, and you can use evaluation tooling to confirm an agent is sound before it goes live.
• You have worked as a technical developer directly alongside business teams, giving you real business fluency: you can map how a function works, translate between the technical and business sides, and bring the acumen to earn credibility and steer toward the right outcomes.
• A track record as a force multiplier: leading a community of practitioners, coaching and training people to adopt new tools and ways of working, and raising the capability of an entire organization rather than delivering all the work yourself.

Preferred

• Deeper hands-on engineering with agentic systems: designing multi-agent orchestration and self-correction, standing up or extending evaluation and test harnesses, and applying standards like MCP and human-in-the-loop controls in production.
• Prior experience on an AI or technology governance body, helpful, though not required given the co-chair nature of the role.
• Experience in a consumer products, health & fitness, or direct-to-consumer e-commerce environment.
• Familiarity with enterprise platforms such as SAP, Salesforce, or Workday, and experience layering AI agents onto them.
• You have created structured training or curriculum materials that people used to onboard themselves without your direct involvement.

WHAT SUCCESS LOOKS LIKE

In the First 90 Days

• AI Governance Committee co-chair role assumed, with guardrails and approved-tool standards drafted for review.
• Community of business AI leaders established, with named leaders across the priority functions and a regular meeting cadence in place.
• Business impact metrics and a prioritized opportunity roadmap defined and shared with leadership.
• Framework for measuring and monitoring production AI, covering performance, quality, responsible behavior, and data security, drafted for executive review.
• At least one hands-on win delivered, a tool, automation, or template in active use and removing a real bottleneck.

By Year One

• Team leaders operating independently, standing up AI-driven workflows in their own business areas without support.
• Community of business AI leaders active and self-sustaining, carrying good practice from one function to the next on its own momentum.
• Adoption and output metrics trending up against targets, with a growing share of automations spanning multiple business areas and owned by the teams that use them.
• Production AI performing reliably and responsibly, monitored against the established framework so issues are caught early.
• Feedback loop operating as a steady rhythm, with field learnings consistently shaping tools, training, and guardrails, and a clear view of what has shipped and what is next.