Head of AI

Stord•Atlanta, GA

1d•Hybrid

About The Position

Stord is seeking a Head of AI to lead the company's artificial intelligence initiatives. This role is central to Stord's growth strategy, focusing on developing AI-powered product experiences and transforming operations through AI. The Head of AI will own the AI product roadmap, lead the AI engineering team, and ensure AI is integrated across the company's products, operations, and engineering practices. This is a senior leadership position reporting to the Head of Engineering, with significant cross-functional collaboration with Product and Data leadership. The role requires a blend of technical expertise, strategic vision, and operational understanding, with the goal of making AI a key differentiator for Stord and its customers.

Requirements

Technical leader who operates like a GM.
Experience building AI products that real users depend on.
Ability to move fast without compromising quality or architecture.
Systems thinking, understanding the connection between model choices, data pipelines, product design, and operational workflows.
Knowledge of LLMs' capabilities and limitations, and when to leverage ML.
Experience designing agentic workflows that function in production.
Experience navigating AI in enterprise software, including reliability challenges, trust issues, and integration complexity.
Ability to own a roadmap, manage a team, and influence cross-functional partners.
Accountability for outcomes, not just activity.
Excitement for the AI-rich domain of supply chain and commerce.

Nice To Haves

Experience in supply chain or commerce domains.

Responsibilities

Own the roadmap and execution for all AI-native product capabilities, including AI PMs and Engineering Teams for AI.
Ensure AI is embedded across Stord's operations, workflows, and engineering practices, partnering with functions like ops, finance, and CX to accelerate AI tooling adoption.
Drive Stord's transition to agentic development, working with the platform team and engineering leadership to make AI-assisted development standard practice.
Own AI architecture decisions, including model selection, agentic pipeline design, LLM integration, inference infrastructure, and AI interaction with the operational data layer.
Bridge AI across product, engineering, and data teams, ensuring data platform investments support AI needs and that product/engineering align with a coherent AI strategy.
Hire, develop, and retain exceptional AI talent, building a team capable of tackling complex problems at scale.