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Job Description

The Director of AI Architecture & Platforms is responsible for defining, implementing, and governing the organization's enterprise AI architecture and technical strategy. This role provides leadership for the design and delivery of scalable, secure, and compliant AI platforms and solutions that enable responsible adoption of generative AI, machine learning, and advanced analytics across the organization.

Reporting to senior IT leadership, the Director establishes architectural standards and reference designs for AI solutions, with a strong emphasis on cloud-native implementation using Amazon Web Services (AWS) and managed AI services such as Amazon Bedrock. The role ensures consistent, reusable, and secure patterns for integrating leading large language models (LLMs), including Anthropic, OpenAI, and Microsoft Copilot, into enterprise applications and workflows.

The Director partners closely with product, application development, data, security, legal, and business leaders to identify, prioritize, and design high-value AI use cases. This role ensures AI solutions are developed with a strong focus on business outcomes, operational readiness, and lifecycle management-from experimentation and prototyping through production deployment and ongoing optimization.

A critical responsibility of the role is establishing and enforcing AI governance frameworks, including policies, controls, and guardrails related to model selection, data usage, risk management, explainability, monitoring, and regulatory compliance. The Director also leads AI-specific cybersecurity and risk considerations, ensuring protections against data leakage, prompt injection, model misuse, and emerging AI threat vectors.

Through technical leadership, architectural rigor, and cross-functional collaboration, the Director enables the organization to adopt AI responsibly, securely, and at scale, while accelerating innovation and delivering measurable business value.

Qualifications

A successful candidate will possess a majority of the following professional and personal attributes and competencies:

• Bachelor's degree or higher required in a relevant field such as Business, or related disciplines required.
• Advanced degree strongly preferred.
• 8-12 years of experience required
• Expert functional skills, advanced industry knowledge and experience, advanced managerial skills
• Manages multiple teams or functions
• Strategic and operational decision-making authority
• Highly complex tasks and managerial tasks
• Minimal supervision

Essential Functions

• Define and lead the enterprise AI architecture strategy, ensuring scalable, secure, and compliant adoption of generative AI and advanced analytics across the organization.
• Design and maintain reference architectures, standards, and patterns for AI solutions, including LLM-enabled applications and platform integrations.
• Provide architectural leadership for AI platforms built on Amazon Web Services (AWS), including the use of managed services such as Amazon Bedrock.
• Lead the evaluation, selection, and integration of leading large language models and AI services, including Anthropic, OpenAI, and Microsoft Copilot, ensuring appropriate use and performance.
• Partner with business, product, and technology leaders to identify, prioritize, and design high-value AI use cases aligned to strategic objectives.
• Establish and enforce AI governance frameworks, including policies, controls, and guardrails related to data usage, model risk, compliance, and responsible AI practices.
• Define and oversee AI cybersecurity architecture, addressing risks such as data leakage, prompt injection, model misuse, and emerging AI threat vectors.
• Provide architectural guidance for the development and integration of AI-enabled applications, ensuring solutions are production-ready, scalable, and maintainable.
• Enable AI lifecycle management practices, including experimentation, deployment, monitoring, optimization, and retirement of AI solutions.
• Collaborate with data, application development, security, legal, and compliance teams to ensure AI solutions align with enterprise standards, regulatory requirements, and risk management expectations.

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