Director, AI Platforms – Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Define and spearhead the strategy, architecture, and engineering capabilities for the organization’s enterprise AI platform.

• Take ownership of the multi-year strategy and reference architecture for data, machine learning, agentic systems, and AI-enabled business intelligence platforms.

• Specify the integration of machine learning and agentic platforms with the enterprise data platform to support business intelligence and agent use cases.

• Create scalable architectures for generative AI, AI agents, traditional machine learning, computer vision, and emerging AI technologies.

• Set standards for enterprise AI architecture, environment specifications, tool/model selection guidelines, and reusable patterns.

• Develop decision-making frameworks for the construction, acquisition, configuration, or partnership for AI capabilities.

• Manage and evolve enterprise AI platforms, services, frameworks, and APIs, encompassing model access, orchestration, knowledge retrieval, observability, identity, and security.

• Establish engineering standards for AI agents, intelligent workflows, APIs, and embedded AI experiences.

• Promote automated testing, continuous integration and delivery, versioning, release management, and production support.

• Implement lifecycle management for predictive models, generative AI applications, and both autonomous and semi-autonomous agents.

• Convert AI governance policies into actionable technical controls.

• Ensure that platform-hosted solutions are governed, awareness of permissions, auditable, and compliant with healthcare data, consumer information, and intellectual property regulations.

• Enforce platform-level safety controls that are proportionate to risk.

• Define production standards and service-level expectations; maintain reliability, availability, and performance.

• Anticipate and manage platform consumption and vendor commitments, including those related to Snowflake/Cortex, cloud services, and model utilization.

• Establish roles, decision-making rights, performance expectations, development plans, and succession readiness.

• Create annual and quarterly operating plans that address priorities, capacity, staffing, funding, vendor relations, technology consumption, and outcomes.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent relevant experience.

• An advanced degree is preferred.

• A minimum of 2 additional years of experience related to the functional area.

• At least 6 years of management experience, including hiring, training, assigning tasks, and evaluating the performance of direct reports.

• Experience in software, data, or machine-learning engineering, cloud platforms, or related fields.

• Proven experience in building and operating production platforms.

• Experience in deploying machine learning or generative AI capabilities at an enterprise scale.

• Strong understanding of contemporary GenAI architectures, foundational models, retrieval-augmented generation, AI agents, and vector technologies.

• Experience in delivering and operating cloud data and AI platforms, such as Snowflake and AWS/Azure.

• Familiarity with large language model stacks, orchestration frameworks, MLOps/LLMOps, continuous integration and delivery, APIs, and observability.

• Experience in defining enterprise architecture standards, reusable platform services, and federated enablement models.

• Solid grounding in responsible AI, security, privacy, and governance within regulated environments.

• Experience managing platform budgets, strategic vendor commitments, and consumption/FinOps.

• Strong executive communication and stakeholder management abilities.

• For remote or hybrid positions, high engagement in virtual environments is essential, including maintaining a camera presence during meetings.

• Must adhere to information security and privacy policies.

• Subject to pre-employment substance abuse testing.

🏝️ Benefits

• Eligible bonuses and commissions may be included as part of the compensation package.

• VSP Vision benefits are available (specific benefits linked in posting).

• Remote work arrangement.