Description:
CYSSC is seeking a consultant role to lead the development of short-term and long-term AI acceleration strategies for the division. This role will focus on creating a comprehensive roadmap for AI adoption establishing governance frameworks and designing scalable technology architectures that align with organizational priorities. The consultant will work closely with senior leadership and cross-functional teams to identify high-value use cases define prioritization criteria and ensure responsible AI practices.
The ideal candidate will bring deep expertise in enterprise architecture AI strategy and data governance combined with strong communication skills to deliver executive-level presentations and actionable plans.
Responsibilities:
- Develop and deliver a comprehensive AI acceleration strategy including short-term and long-term roadmaps.
- Define KPIs and ROI models to measure business impact and technical success of AI initiatives.
- Establish governance frameworks for AI adoption including data strategy compliance and responsible AI principles.
- Assess business value and technical feasibility of AI use cases to guide prioritization.
- Design scalable technical architectures for AI platforms data pipelines and integration patterns.
- Recommend cloud-based AI solutions and establish MLOps practices for model lifecycle management.
- Collaborate with stakeholders to align technical solutions with business objectives and ensure successful delivery.
- Apply enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
- Prepare executive-level presentations and documentation for leadership reviews.
- Provide guidance on vendor selection partnership strategies and emerging AI technologies.
Requirements
Experience and Skill Set Requirements:
Must Haves:
- Experience in developing and executing AI adoption strategies for short-term and long-term horizons.
- Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.
- Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.
- Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.
- Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.
- Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.
Skill Set Requirements:
AI Strategy & Governance:
- Experience in developing and executing AI adoption strategies for short-term and long-term horizons.
- Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.
- Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.
- Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.
- Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments.
- Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks.
- Experience in ensuring adherence to ethical AI standards and regulatory requirements.
- Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery.
- Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders.
- Knowledge of emerging AI trends and ability to assess their relevance for future strategy.
AI Implementation:
- Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.
- Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.
- Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery.
Enterprise Architecture:
- Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
Required Skills:
Experience and Skill Set Requirements: Must Haves: Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Skill Set Requirements: AI Strategy & Governance: Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments. Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks. Experience in ensuring adherence to ethical AI standards and regulatory requirements. Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery. Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders. Knowledge of emerging AI trends and ability to assess their relevance for future strategy. AI Implementation: Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery. Enterprise Architecture: Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
Description:CYSSC is seeking a consultant role to lead the development of short-term and long-term AI acceleration strategies for the division. This role will focus on creating a comprehensive roadmap for AI adoption establishing governance frameworks and designing scalable technology architectures ...
Description:
CYSSC is seeking a consultant role to lead the development of short-term and long-term AI acceleration strategies for the division. This role will focus on creating a comprehensive roadmap for AI adoption establishing governance frameworks and designing scalable technology architectures that align with organizational priorities. The consultant will work closely with senior leadership and cross-functional teams to identify high-value use cases define prioritization criteria and ensure responsible AI practices.
The ideal candidate will bring deep expertise in enterprise architecture AI strategy and data governance combined with strong communication skills to deliver executive-level presentations and actionable plans.
Responsibilities:
- Develop and deliver a comprehensive AI acceleration strategy including short-term and long-term roadmaps.
- Define KPIs and ROI models to measure business impact and technical success of AI initiatives.
- Establish governance frameworks for AI adoption including data strategy compliance and responsible AI principles.
- Assess business value and technical feasibility of AI use cases to guide prioritization.
- Design scalable technical architectures for AI platforms data pipelines and integration patterns.
- Recommend cloud-based AI solutions and establish MLOps practices for model lifecycle management.
- Collaborate with stakeholders to align technical solutions with business objectives and ensure successful delivery.
- Apply enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
- Prepare executive-level presentations and documentation for leadership reviews.
- Provide guidance on vendor selection partnership strategies and emerging AI technologies.
Requirements
Experience and Skill Set Requirements:
Must Haves:
- Experience in developing and executing AI adoption strategies for short-term and long-term horizons.
- Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.
- Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.
- Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.
- Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.
- Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.
Skill Set Requirements:
AI Strategy & Governance:
- Experience in developing and executing AI adoption strategies for short-term and long-term horizons.
- Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success.
- Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles.
- Experience in assessing business value and technical feasibility of AI use cases to guide prioritization.
- Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments.
- Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks.
- Experience in ensuring adherence to ethical AI standards and regulatory requirements.
- Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery.
- Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders.
- Knowledge of emerging AI trends and ability to assess their relevance for future strategy.
AI Implementation:
- Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns.
- Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices.
- Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery.
Enterprise Architecture:
- Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
Required Skills:
Experience and Skill Set Requirements: Must Haves: Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Skill Set Requirements: AI Strategy & Governance: Experience in developing and executing AI adoption strategies for short-term and long-term horizons. Experience in defining and implementing KPI and ROI frameworks to measure business impact and technical success. Experience in designing governance models for AI initiatives including data strategy compliance and responsible AI principles. Experience in assessing business value and technical feasibility of AI use cases to guide prioritization. Ability to guide cultural and operational shifts required for AI adoption including stakeholder alignment and readiness assessments. Experience in identifying risks (bias privacy compliance) and implementing mitigation strategies beyond just governance frameworks. Experience in ensuring adherence to ethical AI standards and regulatory requirements. Ability to evaluate and recommend external AI vendors platforms and academic partnerships for accelerating delivery. Strong ability to translate complex AI concepts into clear actionable insights for senior leadership and non-technical stakeholders. Knowledge of emerging AI trends and ability to assess their relevance for future strategy. AI Implementation: Experience in designing scalable technical architectures for AI platforms data pipelines and integration patterns. Experience in recommending and guiding implementation of cloud-based AI solutions and MLOps practices. Experience in collaborating with stakeholders to align technical solutions with business objectives and ensure successful delivery. Enterprise Architecture: Experience in applying enterprise architecture frameworks (TOGAF Zachman or similar) to align AI initiatives with organizational standards.
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