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Director, Enterprise AI & Machine Learning Engineering

🕒 5 days ago
Agentic AIMachine LearningData ScienceSoftware Engineering
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📜 Description

  • Lead the engineering and machine learning strategy for agentic AI solutions designed to address complex needs of enterprise and retail partners.
  • Build, mentor, and inspire high-performing engineering and science teams, fostering technical excellence, experimentation, collaboration, and strong execution.
  • Partner directly with enterprise customers, product leaders, and data scientists to translate complex business challenges into impactful AI products.
  • Guide the development of production-ready systems combining machine learning, data, software engineering, and agentic AI capabilities.
  • Establish technical direction in a zero-to-one product environment while balancing long-term strategy with rapid experimentation.

🛠️ 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.
  • Strong understanding of machine learning development practices, software engineering principles, and data systems.
  • Deep technical expertise in agentic systems, large language models, or related areas of applied artificial intelligence is preferred.
  • Proven ability to create clarity and momentum in zero-to-one environments while maintaining strong standards for quality.

✨ Benefits

  • Compensation may vary based on location, experience, skills, qualifications, and other relevant factors.
  • Eligibility for a new-hire equity grant.
  • Eligibility for annual equity refresh grants.
  • Competitive compensation and benefits package.
  • Flexible work environment allowing employees to work from home, an office, or another preferred location, subject to applicable policy.
  • Regular opportunities for in-person connection and team-building.
  • Additional benefits available based on work location.
  • Jobgether - Director, Enterprise AI & Machine Learning Engineering
Full job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Enterprise AI & Machine Learning Engineering based in United States.

This role leads the development of next-generation agentic AI solutions designed to solve complex enterprise business challenges. You’ll operate at the intersection of engineering, machine learning, data science, product, consulting, and customer-facing teams. The position combines technical leadership with direct engagement with enterprise partners to identify opportunities and turn them into impactful AI products. You’ll shape technical strategy while guiding teams through the full product lifecycle, from early discovery and experimentation to production deployment and scale. The environment is highly entrepreneurial and zero-to-one, requiring strong judgment, adaptability, and comfort with ambiguity. Your work will help establish new AI capabilities while delivering measurable value to customers and business partners.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1

Accountabilities:

  • Lead the engineering and machine learning strategy for agentic AI solutions designed to address complex needs of enterprise and retail partners.
  • Build, mentor, and inspire high-performing engineering and science teams, fostering technical excellence, experimentation, collaboration, and strong execution.
  • Partner directly with enterprise customers, product leaders, consultants, data scientists, machine learning engineers, and forward-deployed engineers to translate complex business challenges into impactful AI products.
  • Guide the development of production-ready systems combining machine learning, data, software engineering, and agentic AI capabilities, with a focus on reliability, scalability, usability, and measurable customer value.
  • Establish technical direction in a zero-to-one product environment while balancing long-term strategy with rapid experimentation, early deployments, and changing customer requirements.
  • Lead teams through the complete product development lifecycle, from identifying customer needs and evaluating emerging technologies to building, deploying, and scaling AI systems.
  • Represent the Enterprise AI function across the organization by communicating technical tradeoffs, progress, risks, opportunities, and strategic priorities to senior stakeholders.
  • Build alignment across technical, product, commercial, and customer-facing teams around AI strategy and execution.
  • Create clarity and momentum in an evolving environment while maintaining high standards for quality, responsible AI development, and customer impact.
  • Make thoughtful decisions amid ambiguity and continuously adapt technical and product approaches based on customer feedback, business needs, and emerging technologies.
  • 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.
    • Proven ability to partner with product, business, customer-facing, and technical stakeholders to define requirements and deliver solutions to complex problems.
    • Strong understanding of machine learning development practices, software engineering principles, data systems, and the operational requirements involved in scaling AI applications.
    • Demonstrated ability to set technical direction, prioritize initiatives, manage ambiguity, and consistently deliver results in rapidly changing environments.
    • Deep technical expertise in agentic systems, large language models, machine learning platforms, or related areas of applied artificial intelligence is preferred.
    • Experience delivering applied machine learning products at significant scale, including solutions used by external customers or business partners, is preferred.
    • Experience leading cross-functional initiatives spanning engineering, machine learning, data science, product, consulting, and customer-facing teams is preferred.
    • Experience working directly with retailers, commerce platforms, or other enterprise customers to translate operational challenges into technology solutions is preferred.
    • Proven ability to create clarity and momentum in zero-to-one environments while maintaining strong standards for quality, responsible development, and customer value.
    • Strong communication, leadership, collaboration, strategic thinking, and decision-making skills.
    • Benefits:

      • Base salary range of $313,000–$330,500 CAD for Canadian-based candidates.
      • Compensation may vary based on location, experience, skills, qualifications, and other relevant factors.
      • Eligibility for a new-hire equity grant.
      • Eligibility for annual equity refresh grants.
      • Competitive compensation and benefits package.
      • Flexible work environment allowing employees to work from home, an office, or another preferred location, subject to applicable policy.
      • Regular opportunities for in-person connection and team-building.
      • Additional benefits available based on work location.
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