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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, AI Platforms & Engineering - **Company:** Vision Service Plan - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $105,000.0 - $165,375.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, ARM Architecture, Computer Vision, Automation of Tests, Microsoft Azure, Software as a Service, Cloud Database, Information Systems, Continuous Integration, Data Infrastructure, Information Retrieval, Machine Learning, Release Management, Azure Machine Learning, Software Engineering, Management of Software Versions, AI Infrastructure, Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, IT Architecture, Agentic-AI, AI Platforms, Kubernetes, Information Technology, Embedded AI, Machine Learning Operations - **Published:** October 22, 2026 - **Apply:** https://diversityjobs.com/career/18733347/Director-Ai-Platforms-Engineering ## About the Role 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 ## Description remote work United States Oct 23, 2026 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