Director, AI Platforms & Engineering

VSP Vision Care • Cynthian, OH

22h • $105,000 - $165,375

About The Position

The Director, AI Platforms & Engineering defines and leads the organization’s enterprise AI platform strategy, architecture, and engineering capabilities. The role is accountable for the platforms, standards, and governance that enable secure, reliable, and scalable development, deployment, and operation of AI solutions across the organization. It oversees machine learning, agentic AI, and AI-enabled business intelligence platforms, providing a common foundation for innovation while maintaining security, compliance, reliability, and cost efficiency.

The Director owns the multi-year strategy and reference architecture for AI platforms spanning the data platform, ML platform, agentic platform, and AI-enabled BI. The role establishes how these platforms fit together, develops standards and reusable services, and sets decision frameworks for building, buying, configuring, or partnering for AI capabilities. It also leads engineering practices and lifecycle management for predictive models, generative AI applications, and autonomous or semi-autonomous agents.

In partnership with stakeholders, the Director translates AI governance policies into technical controls and ensures platform-hosted solutions are governed, permissions-aware, auditable, and compliant with requirements for healthcare data, consumer information, and intellectual property. The role establishes production and service-level expectations, owns operational reliability, availability, and performance, and manages platform consumption and vendor commitments. It also leads organizational planning and people management, including staffing, development, performance, and succession readiness.

The position requires experience across software, data, or machine-learning engineering, cloud platforms, and production platforms; enterprise-scale AI delivery; architecture and platform standards; responsible AI and governance in regulated environments; and budget, vendor, and consumption management. For remote or hybrid roles, candidates must demonstrate strong engagement in virtual environments, including maintaining camera presence during meetings.

The working environment is generally favorable, with adequate lighting and temperature and no hazardous or unpleasant conditions from noise, dust, or similar factors. The description provides a general indication of the work and is not a comprehensive inventory of all duties or qualifications. The salary range is $105,000 to $165,375. Eligible bonuses and commissions may be included as part of compensation. VSP Vision is an equal opportunity employer and conducts pre-employment substance abuse testing. Employees may have access to sensitive personal information and must follow Information Security and Privacy Policies.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent relevant experience.
• Minimum of 2 additional years of experience related to the functional area.
• Minimum of 6 years of management experience, including hiring, training, assigning work, and managing direct reports’ performance.
• Experience across software, data, or machine-learning engineering, cloud platforms, or related disciplines, including building and operating production platforms.
• Demonstrated experience taking machine learning or generative AI capabilities into production at enterprise scale, with a strong understanding of modern GenAI architectures, foundation models, RAG, AI agents, and vector technologies.
• Experience delivering and operating cloud data and AI platforms such as Snowflake, AWS, or Azure, and modern tooling including LLM stacks, orchestration frameworks, MLOps/LLMOps, CI/CD, APIs, and observability.
• Proven ability to define enterprise architecture standards, reusable platform services, and a federated enablement model adopted across multiple teams.
• Strong grounding in responsible AI, security, privacy, and governance for regulated environments such as healthcare or financial services, including auditability and access control.
• Experience managing platform budgets, strategic vendor commitments, and consumption/FinOps for scaled technology or AI environments.
• Strong executive communication and stakeholder-management skills, including the ability to translate complex technical tradeoffs into clear priorities and delivered outcomes.
• For remote or hybrid roles, ability to demonstrate high engagement in virtual environments, including maintaining camera presence during meetings.

Nice To Haves

• Advanced degree preferred.

Responsibilities

• Own the multi-year strategy and reference architecture for AI platforms spanning the data platform, ML platform, agentic platform, and AI-enabled BI.
• Define how ML and agentic platforms sit on the enterprise data platform and how ML products support BI and agent use cases.
• Establish scalable architecture for generative AI, AI agents, traditional machine learning, computer vision, and emerging AI technologies while preserving optionality across cloud providers, foundation models, and SaaS platforms.
• Set enterprise AI architecture and environment standards, tool and model selection guidelines, and reusable patterns in partnership with Enterprise Architecture.
• Establish decision frameworks for whether to build, buy, configure, or partner for AI capabilities.
• Own and evolve enterprise AI platforms, services, frameworks, and APIs, including model access, orchestration, knowledge retrieval, observability, identity, and security.
• Establish engineering standards for AI agents, intelligent workflows, APIs, and embedded AI experiences.
• Drive software engineering practices including automated testing, CI/CD, versioning, release management, and production support.
• Establish enterprise lifecycle management for predictive models, generative AI applications, and autonomous or semi-autonomous agents.
• Translate AI governance policies into practical technical controls embedded within the platform.
• Partner with stakeholders to ensure platform-hosted solutions are governed, permissions-aware, auditable, and meet requirements for healthcare data, consumer information, and intellectual property.
• Implement platform-level safety controls proportionate to risk.
• Establish production standards and service-level expectations for enterprise AI capabilities, and own operational reliability, availability, and performance.
• Forecast and manage platform consumption and vendor commitments, including Snowflake/Cortex, cloud, and model usage.
• Establish clear roles, decision rights, performance expectations, development plans, and succession readiness; align replacement and future hiring to evolving organizational needs.
• Develop annual and quarterly operating plans covering priorities, capacity, staffing, funding, vendor needs, technology consumption, and anticipated outcomes.

Benefits

• Eligible bonuses and commissions may be included as part of the compensation package.
• VSP Vision benefits are referenced; specific benefits are not listed.

What This Job Offers

• Job Type: Full-time
• Career Level: Director