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.

Work location: 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.

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? 

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