Westcon-Comstor
Website:
westconcomstor.com
Job details:
The AI Delivery & Operations Manager is responsible for ensuring the successful operational delivery, governance, and support of the organization's AI and Intelligent Demand (iD) capabilities. This role serves as the operational backbone of the AI & Analytics function, driving agile delivery processes, managing AI use case intake and reviews, coordinating incident response, overseeing platform administration, and ensuring compliance and operational readiness across AI solutions.
Working closely with D&A Product Owners, IT Infrastructure, Security, Compliance, and Development teams, the AI Delivery & Operations Manager ensures priorities are executed efficiently, risks are identified early, and AI services remain secure, compliant, scalable, and business-focused.
Key Responsibilities
Agile Delivery & Scrum Management
Act as the Scrum Manager for both AI and Intelligent Demand (iD) portfolios, ensuring effective planning, prioritization, and execution of work.
Responsibilities
- Own and manage the AI and iD Jira backlogs, ensuring work items are accurately documented and maintained.
- Facilitate sprint planning, backlog refinement, sprint reviews, and retrospectives.
- Ensure development priorities align with Product Owner objectives and business value.
- Validate that user stories, acceptance criteria, dependencies, and business requirements are sufficiently defined before entering development.
- Monitor sprint progress and proactively identify risks, blockers, and resource constraints.
- Escalate delivery issues, competing priorities, and risks to the Sr. Director of Analytics & AI (AI Chief Product Owner) as appropriate.
- Drive continuous improvement of agile delivery processes and team effectiveness.
AI Use Case Intake, Review & Governance
Own the operational management of the AI use case review process from intake through approval.
Responsibilities
- Serve as the primary coordinator for AI use case submissions across the organization.
- Review proposed use cases for business value, strategic alignment, and expected ROI.
- Conduct preliminary technical feasibility assessments in partnership with AI technical delivery teams.
- Provide recommendations regarding prioritization, solution approach, and implementation readiness.
- Coordinate required compliance, security, and AI governance reviews.
- Track approval status and ensure reviews are completed within agreed service levels.
- Maintain visibility of the AI use case pipeline and provide reporting to leadership.
- Ensure approved use cases have appropriate business sponsorship, success metrics, and implementation plans.
Incident Management & Operational Excellence
Ensure reliable operation of AI and analytics platforms through structured incident response and operational governance.
Responsibilities
- Coordinate real-time response to production incidents, service disruptions, and critical support issues.
- Ensure appropriate troubleshooting, investigation, and escalation paths are followed.
- Act as the operational point of coordination between business, technical, and support teams during incidents.
- Drive post-incident reviews and Root Cause Analysis (RCA) activities.
- Ensure corrective and preventive actions are documented, assigned, and tracked to completion.
- Establish operational standards, monitoring procedures, and service management practices.
- Maintain incident records, operational metrics, and service health reporting.
AI Platform Administration & Access Management
Own operational oversight of AI platform administration and user enablement.
Responsibilities
- Manage the interface with IT Infrastructure team regarding AI platform access & operations.
- Coordinate GenAI licensing requests, provisioning, renewals, and utilization tracking.
- Oversee access management processes for AI platforms, applications, and environments.
- Ensure appropriate controls exist for user onboarding, role assignments, and offboarding.
- Support audits and compliance reviews related to AI platform access and usage.
- Monitor platform adoption and identify opportunities for operational optimization.
Process, Dependency & Governance Management
Ensure operational processes, dependencies, and delivery assets are maintained and consistently applied.
Responsibilities
- Maintain centralized repositories for technical dependencies, implementation checklists, governance requirements, and operational documentation.
- Ensure delivery teams follow established development, deployment, compliance, and release management processes.
- Coordinate cross-functional dependencies between product, engineering, infrastructure, security, and business teams.
- Identify operational risks and implement mitigation plans.
- Establish and maintain standard operating procedures (SOPs) for AI and analytics operations.
- Support internal audits, governance reviews, and leadership reporting requirements.
Key Stakeholder Relationships
- D&A Leadership
- D&A Product Owners
- AI & Analytics Development Teams
- Business Sponsors
- IT Infrastructure & Security Team
- Compliance Functions
- Other D&A and IT Support Teams
Qualifications & Experience
Required
- 5+ years of experience in Agile delivery, Scrum Management, Product Operations, DevOps Operations, or Technology Program Management.
- Experience managing software, analytics, AI, or digital product delivery teams.
- Strong working knowledge of Jira, Agile methodologies, backlog management, and sprint planning.
- Experience coordinating cross-functional technology initiatives involving business and technical stakeholders.
- Strong understanding of incident management, service operations, and root cause analysis processes.
- Experience supporting governance, risk, compliance, or operational review processes.
- Excellent organizational, communication, and stakeholder management skills.
Preferred
- Experience supporting AI, Machine Learning, GenAI, or analytics platforms.
- Scrum Master, Agile, ITIL, or Project Management certifications.
- Experience with AI governance, responsible AI frameworks, privacy reviews, or regulatory compliance.
- Familiarity with cloud platforms and identity/access management processes.
Success Measures
The AI Delivery & Operations Manager will be measured by:
- Sprint predictability and on-time delivery of prioritized work.
- Backlog quality and readiness of work entering development.
- AI use case review cycle times and governance compliance rates.
- Incident response effectiveness and resolution times.
- Completion of RCAs and preventive actions.
- AI platform license utilization and access management accuracy.
- Reduction in operational risks and delivery bottlenecks.
- Stakeholder satisfaction across business, product, and technical teams.
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