Director, Enterprise AI & Machine Learning Engineering
New
J
JobgetherEnterprise AI
Based in United StatesFull-TimeDirector
SalaryBase salary range of $313,000–$330,500 CAD for Canadian-based candidates.
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Job Details
- Required Skills
- Machine LearningProduct DevelopmentSoftware EngineeringLLMGenerative AI
Requirements
- Demonstrated experience building and deploying agentic AI, generative AI, or machine learning products in production environments.
- Experience leading engineering, machine learning, data science, or applied science teams through product development and delivery.
- Ability to partner with product, business, customer-facing, and technical stakeholders to define requirements and deliver solutions.
- Strong understanding of machine learning development practices, software engineering principles, and data systems.
- Understanding of operational requirements for scaling AI applications.
- Ability to set technical direction, prioritize initiatives, manage ambiguity, and deliver results in changing environments.
- Deep expertise in agentic systems, large language models, machine learning platforms, or related applied AI areas is preferred.
- Experience delivering applied machine learning products at significant scale, including products used by external customers or business partners, is preferred.
- Experience leading cross-functional initiatives across engineering, machine learning, data science, product, consulting, and customer-facing teams is preferred.
- Experience working with retailers, commerce platforms, or other enterprise customers to translate operational challenges into technology solutions is preferred.
- Ability to create clarity and momentum in zero-to-one environments while maintaining standards for quality, responsible development, and customer value.
Responsibilities
- Lead engineering and machine learning strategy for agentic AI solutions serving enterprise and retail partners.
- Build, mentor, and guide engineering and science teams.
- Partner with enterprise customers and cross-functional stakeholders to turn business challenges into AI products.
- Guide development of production-ready systems combining machine learning, data, software engineering, and agentic AI.
- Set technical direction while balancing strategy, experimentation, early deployments, and changing customer requirements.
- Lead the product lifecycle from identifying customer needs through building, deploying, and scaling AI systems.
- Communicate technical tradeoffs, progress, risks, opportunities, and priorities to senior stakeholders.
- Align technical, product, commercial, and customer-facing teams around AI strategy and execution.
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