AI Enablement & Solutions Lead

K18 Hair

15h • $120,000 - $145,000

About The Position

At K18, we're about hair freedom for all–engineered with biotech. We are on a mission to liberate expression. To make the impossible possible with the right technology. To build a community of forward thinkers, risk takers, and rabble rousers. To bring fearless innovation forward and push boundaries past where we thought they could go. K18 is a biotech haircare company on a mission to unlock hair’s full potential through science. We’re a fast-moving, category-defining brand — and we’re building an AI-forward culture where smart automation and thoughtful tooling help our teams move faster and focus on the work that matters most. We're looking for an AI Enablement & Solutions Lead to own how AI gets applied across the business. This role turns ideas into real, usable solutions that drive efficiency, improve decision-making, and unlock new capabilities across teams. This is not a research or strategy-only role. You will identify high-impact use cases, build and prototype solutions directly, and partner with data science and analytics to scale what works. You'll act as the connective tissue between business teams, Data Science & Analytics, and IT, ensuring AI is applied in a practical, measurable, and responsible way.

Requirements

• 5-8+ years in a technical, product, or analytics role
• Proven, hands-on experience building AI or LLM-based solutions, not just familiarity with the concepts
• Comfortable in Python and working with APIs and data pipelines
• Track record of taking ideas from concept to working solution
• Ability to define problems clearly and prioritize decisively to focus on high-impact work
• Translates business needs into technical requirements, and vice versa
• Focused on measurable impact, not just building interesting technology
• Hands-on experience building AI agents or agentic workflows (e.g., LangGraph, CrewAI, AutoGen, or similar frameworks) is strongly preferred
• Working knowledge of LLMs, prompt design, embeddings, and/or retrieval-augmented generation (RAG)
• Hands-on experience with Databricks or a similar modern data platform is strongly preferred
• Familiarity with Azure (e.g., Azure OpenAI, Azure ML, or Azure DevOps) and basic DevOps practices (CI/CD, version control, deployment pipelines) is a plus
• Explains complex AI concepts clearly to non-technical stakeholders
• Comfortable working cross-functionally and driving alignment without formal authority
• Advocates for simple, practical solutions and helps the team avoid over-engineering

Nice To Haves

• Hands-on experience building AI agents or agentic workflows (e.g., LangGraph, CrewAI, AutoGen, or similar frameworks) is strongly preferred
• Hands-on experience with Databricks or a similar modern data platform is strongly preferred
• Familiarity with Azure (e.g., Azure OpenAI, Azure ML, or Azure DevOps) and basic DevOps practices (CI/CD, version control, deployment pipelines) is a plus

Responsibilities

• Own AI Use Cases End-to-End
• Partner with marketing, eCommerce, creative, operations, and finance to surface high-impact AI opportunities
• Translate ambiguous business problems into clearly scoped use cases and workflows
• Prioritize initiatives based on business value, feasibility, and data readiness
• Design and build AI agents and multi-step agentic workflows that automate decisions, surface insights, and take action across business processes
• Prototype quickly using agent frameworks (e.g., LangGraph, CrewAI, or similar) alongside LLM APIs (OpenAI, Claude, etc.) and lightweight front-end tooling (e.g., Gradio, Chainlit)
• Validate ideas quickly and cheaply before committing to full-scale development
• Partner with Data Science & Analytics and IT to productionize successful prototypes
• Define clear inputs, outputs, and success metrics for each solution
• Ensure solutions are reliable, maintainable, and built to last beyond the pilot
• Enable teams to use AI tools effectively through training, documentation, and playbooks
• Embed solutions into existing workflows, not as standalone tools, but as integrated capabilities
• Track adoption and outcomes; iterate until solutions are actually delivering value
• Define clear standards for when and how AI should be used across the organization
• Ensure responsible AI use: data privacy, output quality, bias awareness, and appropriate human oversight
• Standardize tools and approaches to reduce fragmentation and technical debt

Benefits

• This range represents the low and end of the anticipated base salary range for this position. The actual base salary will depend on numerous factors such as: experience, knowledge and skills, and if the location of the job changes.

What This Job Offers

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