Director, AI Foundations Engineering

Accountabilities:

• • Lead the design, development, operation, and continuous improvement of the foundational AI capabilities supporting agentic AI use cases and intelligent workflows.
  • Define and implement an agentic AI foundation, including engineering standards, development practices, operating models, and technical approaches that promote scalability, reliability, repeatability, security, and continuous improvement.
  • Establish a clear engineering strategy and roadmap for core AI capabilities, ensuring priorities align with enterprise needs and strategic objectives.
  • Oversee engineering teams responsible for developing reusable platform services, tools, frameworks, and components that enable AI-powered products and workflows.
  • Partner closely with product, data, infrastructure, security, technology, innovation, and business teams to translate enterprise requirements into scalable technical solutions.
  • Drive modernization and integration initiatives that connect existing systems, products, services, and processes with AI capabilities.
  • Establish effective operational support models, governance practices, monitoring mechanisms, and processes that ensure reliable and consistent delivery of AI capabilities.
  • Monitor agentic AI operations, system performance, user feedback, and emerging requirements to identify opportunities for optimization and improvement.
  • Identify technical risks, operational challenges, dependencies, and investment requirements, developing recommendations and mitigation strategies for senior leadership.
  • Communicate platform priorities, roadmap progress, delivery status, technical risks, and investment needs clearly to executives and cross-functional stakeholders.
  • Promote disciplined engineering practices that enable resilient, extensible, maintainable, and high-performing AI services.
  • Lead organizational change and adoption efforts that help teams incorporate new AI capabilities into existing workflows and operating models.
  • Mentor and develop engineering and product-oriented leaders, encouraging strong technical practices, collaboration, accountability, experimentation, and continuous learning.
  • Connect AI platform investments and engineering decisions to measurable business value, enterprise adoption, operational efficiency, and innovation outcomes.

  Requirements:

  • Bachelor’s degree in business, engineering, computer science, data science, or a related field is required; an advanced degree is preferred.
  • 8+ years of experience in AI engineering, with a strong track record of leading strategy, roadmaps, and delivery for complex digital, data, or AI-enabled products and platforms.
  • Demonstrated experience working in AI- and data-driven product environments, translating business needs into scalable technical solutions and partnering with engineering teams to deliver innovative products.
  • Strong understanding of AI engineering, machine learning, data-driven products, AI platforms, intelligent workflows, and enterprise technology ecosystems.
  • Proven ability to lead engineering strategy and establish scalable development standards, operating models, governance practices, and technical roadmaps.
  • Experience building or scaling reusable AI services, platform capabilities, tools, or components that support multiple products, teams, or business use cases.
  • Strong cross-functional leadership skills, with the ability to build alignment across Engineering, Innovation, Design, Data Science, Commercial, Product, and other business functions.
  • Demonstrated ability to influence senior stakeholders, communicate complex technical concepts clearly, and make informed decisions involving priorities, trade-offs, risks, and investments.
  • Experience managing, mentoring, and developing product managers, technical leaders, or other junior leaders, including coaching and prioritization support.
  • Strong strategic, analytical, and problem-solving skills, with the ability to connect technical decisions to business outcomes.
  • Experience with AI, machine learning, data science, data governance, data quality, statistical analysis, or related disciplines is highly valuable.
  • Strong change management, stakeholder engagement, mentorship, learning agility, and curiosity are important for success in this role.
  • Ability to operate effectively in a rapidly evolving environment where emerging AI technologies, business requirements, and enterprise priorities continuously change.

  Benefits:

  • Base salary: $194,600–$361,400 USD per year, with final compensation determined by relevant skills, experience, and other applicable factors.
  • Performance incentive: Eligibility for performance-based cash compensation.
  • Equity: Depending on role level, eligibility to be considered for annual equity awards.
  • Healthcare: Comprehensive health benefits for eligible US-based employees.
  • Insurance: Life and disability benefits.
  • Retirement: 401(k) plan with company contribution and matching.
  • Paid time off: Generous vacation, personal days, holidays, and other leave programs.
  • Remote anywhere in the United States, subject to applicable legal-entity restrictions.
  • Travel: Domestic and/or international travel requirements will be determined by the hiring manager.
  • Career development: Opportunity to lead high-impact AI initiatives, mentor technical talent, and shape enterprise engineering practices.
  • Innovation environment: Work at the forefront of agentic AI, machine learning, data-driven products, and enterprise digital transformation.