Director, AI Platforms & Engineering

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

Own the multi-year strategy and reference architecture for the organization’s AI platforms, spanning the data platform, ML platform, agentic platform, and AI-enabled BI

Define how the ML and agentic platforms sit on top of the enterprise data platform, and how ML products support BI and agent use cases, to present a coherent platform and capabilities journey
Establish a scalable architecture for generative AI, AI agents, traditional machine learning, computer vision, and emerging AI technologies that preserves optionality across cloud providers, foundation models, and SaaS platforms
Set enterprise AI architecture standards, environment standards, tool/model selection guidelines, and reusable patterns in partnership with Enterprise Architecture
Establish clear decision frameworks for when the organization should build, buy, configure, or partner for AI capabilities
Own and evolve enterprise AI platforms, services, frameworks, and APIs that enable scalable AI development and operations, including model access, orchestration, knowledge retrieval, observability, identity, and security
Establish engineering standards for AI agents, intelligent workflows, APIs, and embedded AI experiences
Drive disciplined 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 organization’s AI governance policies into practical technical controls embedded within the platform
In partnership with various stakeholders, ensure platform-hosted solutions are governed, permissions-aware, and 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 (e.g., Snowflake/Cortex, cloud, and model usage)
Establish clear roles, decision rights, performance expectations, development plans, and succession readiness; Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent relevant experience; Minimum of 6 years of management experience with responsibilities for hiring, training, assigning work, and managing performance of direct reports
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 strong understanding of modern GenAI architectures, foundation models, RAG, AI agents, and vector technologies
Experience delivering and operating cloud data and AI platforms (e.g., Snowflake, AWS, 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 (e.g., 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
For roles that are remote (i.e., Work From Home (WFH)) or hybrid (i.e., partial onsite at a VSP location and WFH), must demonstrate a high level of engagement in virtual environments, including maintaining camera presence during meetings to support effective communication and team alignment
As a part of the compensation package, this role may include eligible bonuses and commissions. Salary Ranges: $105,000.00 - $165,375.00 VSP Vision is an equal opportunity employer and gives consideration for employment to qualified applicants without regard to age, gender, race, color, religion, sex, national origin, disability or protected veteran status. Unincorporated LA County Residents: Fraud Alert - Fake Job Opportunity Solicitations Used to Collect Fees/Personal Information.

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