Director, AI Platforms & Engineering

Posted Yesterday
Hiring Remotely in US
Remote
105K-165K Annually
Senior level
Healthtech • Insurance • Retail • Social Impact
The Role
Leads enterprise AI platform strategy, architecture, engineering, governance, and operations across machine learning, generative AI, agents, data, and business intelligence. Owns platform standards, reusable services, lifecycle management, security, compliance, reliability, vendor commitments, budgets, and consumption. Directs production-scale AI enablement, establishes responsible AI controls, and manages engineering teams, staffing, operating plans, and executive stakeholder alignment.
Summary Generated by Built In
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; 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


Job Specifications

 

Typically has the following skills or abilities:


Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent relevant experience; advanced degree preferred; Minimum of 2 additional years of experience related to functional area


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


Strong executive communication and stakeholder-management skills, with the ability to translate complex technical tradeoffs into clear priorities and delivered outcomes


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

 

Working Conditions


The working environment is generally favorable lighting and temperature is adequate, and there are no hazardous or unpleasant conditions caused by noise, dust, etc.


The above information on this description has been designed to indicate the general nature and level of work performed by employees within this classification.  It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job grade

#LI-VISIONCARE

Compensation range for the role is listed below. Applicable salary ranges may differ across markets. Actual pay will be determined based on experience and other job-related factors permitted by law. As a part of the compensation package, this role may include eligible bonuses and commissions. For more information regarding VSP Vision benefits, please click here. 

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.  We maintain a drug-free workplace and perform pre-employment substance abuse testing. 

Unincorporated LA County Residents: Qualified Applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act, and any other similar laws.

Notice to Candidates: Fraud Alert - Fake Job Opportunity Solicitations Used to Collect Fees/Personal Information. 


We have been made aware that fake job opportunities are being offered by individuals posing as VSP Vision and affiliate recruiters. Click here to learn about our application process and what to watch for regarding false job opportunities. 

As a regular part of doing business, VSP Vision (“VSP”) collects many different types of personal information, including protected health information, about our audiences, including members, doctors, clients, brokers, business partners, and employees.  VSP Vision employees will have access to this sensitive personal information and are subject to follow Information Security and Privacy Policies. 

Skills Required

  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent relevant experience
  • Minimum of two additional years of experience related to the functional area
  • Advanced degree
  • At least six years of management experience, including hiring, training, work assignment, and performance management
  • Experience across software, data, machine-learning engineering, cloud platforms, or related disciplines, including production platform development and operations
  • Experience deploying machine learning or generative AI capabilities into production at enterprise scale
  • Strong understanding of modern generative AI architectures, foundation models, RAG, AI agents, and vector technologies
  • Experience delivering and operating cloud data and AI platforms, including Snowflake or AWS/Azure environments
  • Experience with LLM stacks, orchestration frameworks, MLOps/LLMOps, CI/CD, APIs, and observability
  • Experience defining enterprise architecture standards, reusable platform services, and federated enablement models
  • Knowledge of responsible AI, security, privacy, governance, auditability, and access control in regulated environments
  • Experience managing platform budgets, strategic vendor commitments, and technology or AI consumption/FinOps
  • Strong executive communication and stakeholder-management skills
  • High engagement in virtual environments, including camera presence during meetings, for remote or hybrid roles
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The Company
HQ: Rancho Cordova, CA
13,052 Employees
Year Founded: 1955

What We Do

VSP Vision Care is a not-for-profit organization founded in 1955, providing vision benefits, eye care insurance, eyewear, and lenses, and reinvesting in communities.

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