Director, AI Solutions & Delivery | 1060514

The Director, AI Solutions & Delivery is responsible for leading the enterprise AI portfolio and overseeing the identification, design, prioritization, and delivery of AI solutions that create measurable business value. This role serves as the bridge between business strategy and technical execution, partnering with business leaders to evaluate opportunities, define AI roadmaps, and recommend the most appropriate AI technologies, platforms, and architectures for each use case.
 
Beyond the core responsibilities outlined in the job description, we’re looking for a highly driven transformation leader who has successfully led enterprise-scale digital transformation initiatives and understands what it takes to build and operationalize new capabilities across an organization.
 

• The ideal candidate has experience designing governance frameworks, establishing operating models, and driving cross-functional adoption to ensure new capabilities are scalable, sustainable, and aligned with business objectives.
• They are comfortable navigating organizational change, influencing senior stakeholders, and bringing together business and technology teams to deliver measurable outcomes.
• We are also seeking someone who is genuinely AI-curious and passionate about the rapidly evolving AI landscape.
• They should have hands-on experience evaluating, implementing, or scaling AI tools, platforms, or solutions within an enterprise environment and be excited to continuously learn and stay current on emerging technologies, industry trends, and best practices. Most importantly, they can translate AI innovation into practical business value while helping foster a culture of responsible AI adoption across the organization.

 
Essential Duties and Responsibilities: 

• The Director will establish and manage the enterprise AI intake process, maintain the AI use-case portfolio, oversee AI governance and solution standards, and lead the teams responsible for AI engineering, solution development, and AI platform administration.
• The role combines strategic leadership, enterprise architecture, product management, and delivery oversight to ensure AI investments are aligned with business priorities and delivered in a scalable, secure, and sustainable manner.

AI Strategy, Portfolio & Demand Management

• Establish and manage the enterprise AI intake and evaluation framework.
• Build and maintain a centralized inventory of AI opportunities and use cases.
• Develop prioritization methodologies based on business value, feasibility, risk, and strategic alignment.
• Partner with business leaders to identify opportunities for AI-driven transformation.
• Create and maintain the enterprise AI roadmap.
• Track value realization and business outcomes across the AI portfolio.
• Present portfolio recommendations and investment priorities to executive leadership.

 
AI Solution Design & Architecture

• Lead assessment of business problems and determine the most appropriate AI solution approach.
• Evaluate and recommend AI technologies, platforms, models, and vendors.
• Translate business requirements into scalable AI solution architectures.
• Define enterprise standards for:
• Generative AI
• Agentic AI
• Machine Learning
• Intelligent Automation
• Knowledge Management
• AI-enabled workflows
• Establish architecture review processes for AI initiatives.
• Drive build-vs-buy decisions and technology selection.

 
AI Delivery Leadership

• Own end-to-end delivery of enterprise AI initiatives.
• Lead AI solution planning, execution, and implementation activities.
• Ensure AI projects meet business objectives, timelines, budgets, and quality standards.
• Define delivery methodologies and lifecycle processes for AI projects.
• Establish repeatable frameworks for scaling AI solutions across business functions.
• Oversee solution testing, validation, and production readiness.

 
AI Engineering & Platform Leadership

• Lead and develop AI Engineers, Solution Architects, and AI Platform Administrators.
• Establish engineering standards and development practices.
• Oversee enterprise AI platform operations and governance.
• Ensure secure and scalable deployment of AI technologies.
• Guide architecture decisions across AI platforms and applications.
• Drive continuous improvement of AI development capabilities and tooling.

 
AI Governance, Security, Compliance & Risk Management

• Partner with Information Security and Legal to ensure AI deployments meet security, privacy, and regulatory requirements
• Partner with Information Security & Legal to establish enterprise standards and governance processes for AI solutions.
• Ensure AI solutions comply with security, privacy, legal, and regulatory requirements.
• Define responsible AI principles and implementation standards.
• Lead AI architecture review and governance boards.
• Assess technical and operational risks associated with AI initiatives.
• Implement controls for monitoring, auditing, and managing AI solutions.
• Assess and mitigate AI-related risks, including data leakage, IP exposure, and model misuse.

 
Vendor & Technology Management

• Evaluate emerging AI technologies and market offerings.
• Manage relationships with AI vendors and strategic partners.
• Assess platform capabilities and roadmap alignment.
• Support licensing, budgeting, and investment decisions.
• Develop technology recommendations for future AI capabilities.

 
Measurement & Continuous Improvement

• Define KPIs to measure AI adoption, value realization, productivity impact, and risk.
• Monitor usage trends and performance, iterating on configuration and strategy.
• Stay current with emerging generative AI technologies and assess their applicability to the organization.

 
Qualifications:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.  The requirements listed below are representative of the knowledge, skill and/or ability required.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
 
Education and/or Work Experience: 

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (Master’s preferred).
• 10+ years of experience leading technology, analytics, digital transformation, or enterprise application initiatives.
• 5+ years leading solution architecture, product delivery, or enterprise technology programs.
• 3+ years of experience designing and implementing AI, machine learning, or generative AI solutions.
• Experience building and managing technology portfolios and investment roadmaps.
• Proven experience leading cross-functional teams and enterprise initiatives.
• Experience translating business strategy into technology solutions.
• Demonstrated success managing technical delivery teams.
• Direct experience deploying ChatGPT, Claude, or similar enterprise generative AI platforms.
• Familiarity with data governance, privacy frameworks, and responsible AI practices.
• Background in change management or large-scale technology adoption initiatives.
• Demonstrated experience deploying and scaling enterprise SaaS or cloud-based platforms.
• Strong understanding of cloud infrastructure, identity management, APIs, and enterprise security principles.
• Proven ability to operate at both strategic and execution levels.
• Experience influencing decisions across cross-functional stakeholders
• Change management experience and ability to drive adoption of tools/solutions
• Leadership and/or oversight of architects & developers designing individual components of a solution
• Proven success in requirements elicitation & comprehension to deliver the right technical solutions
• Experience in B2B, manufacturing, or enterprise commercial environments.
• Process driven mindset & focus
• Facilitation & communication skills to work across all levels in the organization
• Ability to define problems, collect data, establish facts, and draw valid conclusions
• Work well with peers, and superiors in all departments as well as external contacts

 
Technical Skills and Core Competencies:

1. Generative AI & LLM Platform Expertise

The AI Director must have hands-on experience with enterprise-grade generative AI platforms, including:

• Deep understanding of Large Language Models (LLMs) and how they behave in enterprise settings:
• Prompt engineering and prompt lifecycle management
• Context windows, embeddings, retrieval-augmented generation (RAG)
• Model limitations, hallucinations, and mitigation strategies
• Practical experience deploying and operating:
• ChatGPT Enterprise
• Comparable LLM platforms (Anthropic, Copilot, Google AI, etc.)
• Model selection and tuning tradeoffs:
• Performance vs. cost
• Latency considerations
• Model versioning and lifecycle management

1. Environment Provisioning

This role requires direct ownership of the AI environment, not delegation.

• Strong hands-on experience with cloud platforms, particularly:
• Azure, AWS, or GCP
• Ability to provision and manage:
• Resource groups / projects
• Networking (VNETs/VPCs, private endpoints, firewalls)
• Compute resources for AI workloads
• Cost management and optimization for AI workloads:
• Token usage monitoring
• Quotas and rate limiting
• Budget alerts and cost allocation

1. Identity, Access Management & Enterprise Integration

The AI Director must ensure secure, controlled access at scale.

• Identity and Access Management (IAM):
• Azure AD / Entra ID or equivalent
• SSO integration with enterprise identity providers
• Role-Based Access Control (RBAC)
• Secure integration patterns:
• OAuth 2.0 / OpenID Connect
• API authentication and authorization
• Enterprise system integration:
• Microsoft 365, SharePoint, Teams
• Internal applications via REST APIs
• Workflow automation tools (Power Automate, Logic Apps)

 

1. DevOps, MLOps & Operational Excellence

AI must be operable and supportable, not experimental.

• CI/CD pipelines for AI services and integrations
• Environment promotion where applicable (dev → test → prod)
• Monitoring and observability:
• Latency, errors, throughput
• Usage patterns and anomalies
• Incident response and troubleshooting:
• Model degradation
• Integration failures
• Change management and release controls

 

1. Programming & Automation

While not a full-time developer, the AI Director must be comfortable building and debugging.

• Proficiency in:
• Python (primary)
• JavaScript / TypeScript (for integrations and tooling)
• API development and consumption:
• REST APIs
• Webhooks
• Scripting and automation:
• Environment setup
• Data ingestion
• Monitoring and reporting

 

1. Architecture & Technical Decision-Making

The AI Director must be able to design, defend, and evolve the architecture.

• Ability to create:
• End-to-end solution architectures
• Security and data flow diagrams
• Evaluate tradeoffs between:
• Centralized vs federated AI models
• Build vs buy
• Speed vs control
• Translate business use cases into technical designs

 
 
Travel:

• 15% travel required

Reference: 1060514

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Revel IT, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your experience doesn’t align perfectly with every qualification in the description, we encourage you to apply anyway. You might be the right candidate for this or our other open roles!  

Revel IT is an Equal Opportunity Employer. Revel IT does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

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