New opportunity

Senior Digital Solutions Analyst, AI Programs and Platforms

Northeastern University · Boston, United States

About this role

Northeastern University seeks a senior digital solutions analyst to help staff, faculty, and students adopt AI programs and platforms in administrative and academic workflows. Reporting to the deputy CIO and associate vice president for engagement and experience, the role combines business analysis, solution engineering, consulting, and platform/product ownership. Tools include Copilot, Claude, and other AI-enabled services.

Responsibilities

Gather requirements and engage stakeholders to identify needs, demonstrate AI tools, design solutions, and support adoption.
Help manage AI platforms and digital solutions throughout their lifecycle, including roadmaps, enhancements, user support, and change management. Plan, configure, deploy, document, and support AI-enabled solutions with the digital solutions team.
Develop and deliver training, documentation, and enablement programs. Monitor usage, collect feedback, research emerging tools, and improve programs and platforms.
Support 24/7 business continuity through rotating availability outside normal hours. Monitor system health, respond to alerts and incidents, troubleshoot performance, implement emergency fixes, and coordinate service restoration. Other duties may include knowledge management, data preparation, and AI improvement projects.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Business, or a related field; at least 5 years in IT business analysis, digital solutions engineering, or product/platform ownership, including at least 1 year focused on AI/ML systems or digital transformation.
Experience with AI tools and platforms such as Copilot, Claude, Microsoft 365, ServiceNow, Miro, Qualtrics, or cloud AI services. Advanced requirements gathering, process mapping, solution design, and technical documentation skills; experience implementing solutions for diverse users and delivering technology training.
Strong consulting, stakeholder engagement, communication, collaboration, customer service, platform monitoring, and incident troubleshooting skills. Familiarity with DevOps, MLOps, or CI/CD principles. Relevant technical certifications are preferred.

The position is hybrid, requiring at least three days per week in the Boston office. Applicants must be authorized to work in the United States; the university cannot sponsor work authorization now or in the future. The expected hiring range is $99,010.00–$143,567.50. Eligible employees receive benefits including medical, vision, dental, paid time off, tuition assistance, retirement, and commuting and transportation benefits.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI program enablementAI platform ownershipBusiness analysisRequirements gatheringProcess mappingSolution designDigital solutions engineeringStakeholder engagementTechnical documentationChange managementUser trainingMicrosoft CopilotClaudeMicrosoft 365ServiceNowMiroQualtricsCloud AI servicesPlatform monitoringIncident responseTroubleshootingDevOpsMLOpsCI/CDCommunicationCollaboration

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Translate university needs into AI solutions
Lead requirements gathering and stakeholder alignment with staff, faculty, and students; map workflows and turn needs into solution designs and technical specifications.
Implement and support AI-enabled workflows
Plan, configure, deploy, document, and support solutions with the digital solutions team, including tools such as Copilot and Claude.
Own the platform lifecycle
Help shape roadmaps, enhancements, user support, and change management. Use usage data, feedback, and research on emerging tools to improve platforms.
Enable adoption across user groups
Demonstrate tools and develop training, documentation, and enablement programs for administrative and academic users.
Maintain service continuity
Take part in rotating availability outside normal hours; monitor platform health, triage incidents by business impact, troubleshoot, and coordinate service restoration.

Likely challenges to think through

Reconciling different workflows
A likely difficulty is finding a useful solution when staff, faculty, and students have different needs. Prepare an example of how to compare stakeholder requests, map the underlying workflows, and agree on a practical scope.
Balancing new tools with platform stability
Researching emerging AI tools while managing roadmaps and existing services may create competing demands. Prepare to explain how you would weigh usage evidence and feedback against support effort and the risk of change; this is a preparation hypothesis, not a stated university problem.
Improving adoption without neglecting incidents
Training and solution work may compete with urgent alerts during rotating coverage. Prepare a concrete approach to impact-based triage, coordination with technical teams, service restoration, and communicating follow-up to users.

Practice your answers

Technical practice

How would you gather requirements for an AI-enabled academic or administrative workflow?

What to coverThe posting calls for leading requirements gathering and working with staff, faculty, and students. Suggested preparation: explain how you would map the current process, distinguish user needs from proposed solutions, and turn agreed needs into testable requirements.

How would you evaluate whether Copilot, Claude, or another AI-enabled tool fits a use case?

What to coverThe role includes demonstrating AI tools and facilitating solutions for university users. Suggested preparation: compare the workflow fit, usability, limitations, and support implications of plausible options without assuming any particular tool must be selected.

How would you plan, configure, and deploy an AI-enabled solution?

What to coverThe posting assigns solution planning, configuration, deployment, and user support to this role and its team. Suggested preparation: walk through design decisions, validation with users, deployment readiness, and how you would handle issues found after launch.

How do you translate stakeholder needs into technical specifications and documentation?

What to coverAdvanced solution design and technical documentation are stated qualifications. Suggested preparation: distinguish documentation for implementers from guidance for users, and explain how you would verify that both reflect the agreed workflow.

How would you prioritize a platform roadmap and manage an enhancement?

What to coverThe role helps own AI platform lifecycles, including roadmaps, enhancements, user support, and change management. Suggested preparation: describe how you would weigh user needs, operational impact, effort, and change-readiness when deciding what to do next.

How would you design training for staff, faculty, and students adopting an AI tool?

What to coverDeveloping and delivering training, documentation, and enablement is a stated responsibility. Suggested preparation: explain how you would adapt examples and delivery to different workflows, then check whether users can apply what they learned.

How would you use platform usage and feedback to guide improvements?

What to coverThe posting calls for monitoring usage, collecting feedback, and researching new tools and trends. Suggested preparation: explain how you would interpret usage alongside qualitative feedback, investigate low adoption, and decide whether to improve training, the solution, or both.

How would you respond to an AI platform alert during rotating out-of-hours availability?

What to coverThe role includes monitoring system health, troubleshooting incidents, prioritizing by business impact, and coordinating service restoration. Suggested preparation: outline triage, communication, an emergency-fix decision, and follow-up to reduce recurrence.

How would DevOps, MLOps, or CI/CD principles inform changes to an AI platform?

What to coverThe posting asks for familiarity with these principles as applied to AI systems and digital platforms. Suggested preparation: discuss controlled changes, validation, monitoring, and recovery, while making clear that the posting does not prescribe a particular pipeline or tool.

Behavioural practice

Tell me about a time different stakeholder groups wanted conflicting outcomes from a technology solution.

What to coverThe role leads stakeholder alignment across diverse university users. Suggested preparation: use a real situation, describe how you clarified priorities and reached a decision, and state the result.

Tell me about a time you helped people adopt an unfamiliar technology.

What to coverTraining and enablement are central to the advertised role. Suggested preparation: describe the audience and initial obstacle, what you changed in your training or support, and the observed result.

Tell me about a time you delivered a solution with both end-users and a technical team.

What to coverThe role bridges users and IT and works independently as well as cross-functionally. Suggested preparation: identify the situation, your specific actions to keep needs and implementation aligned, and the outcome.

Tell me about a time you handled a service incident under time pressure.

What to coverThe posting emphasizes incident troubleshooting, business-impact prioritization, and service continuity. Suggested preparation: explain the situation, your triage and communication actions, and the restoration result without overstating your personal role.

Tell me about a time changing needs forced you to revise a platform or project plan.

What to coverThe role includes roadmap changes, continuous improvement, and flexibility as the AI ecosystem evolves. Suggested preparation: describe what changed, how you assessed the trade-offs and coordinated the response, and what resulted.

Sharpen your knowledge

Topics to prepare

User-centered AI adoption
The posting calls for AI adoption across staff, faculty, and students in administrative and academic workflows. Revision exercise: for one hypothetical workflow, outline how each group’s needs might differ and what you would ask before proposing a solution. The workflow is a practice scenario, not a stated university project.
AI platform and product lifecycle
The role includes roadmaps, enhancements, user support, and change management. Revision exercise: sketch how you would prioritize three hypothetical enhancement requests against user impact, effort, and support needs.
Service continuity and incident priorities
The posting specifies rotating availability outside normal hours, health monitoring, alerts, emergency fixes, and service restoration. Revision exercise: work through a hypothetical AI-platform outage and explain how business impact would guide triage, escalation, and updates to users.
DevOps, MLOps, and CI/CD principles
Familiarity with these principles as applied to AI systems and digital platforms is listed as a qualification. Revision exercise: explain, at a conceptual level, how a proposed platform change could be tested, deployed, monitored, and improved; no specific delivery tooling is required by the posting.

Skills to revise

Requirements gathering and process mapping
Advanced proficiency is explicitly requested. Practice a short stakeholder interview for a hypothetical university workflow, then produce a current-state map, a proposed-state map, and five testable requirements.
AI tool demonstration and solution design
The role involves demonstrating AI tools and designing AI-enabled solutions; Copilot and Claude are named examples. Prepare a five-minute, hypothetical use-case walkthrough that explains the user need, proposed workflow, and questions to resolve before implementation. Do not assume a particular university configuration.
Solution documentation and user support
The analyst helps plan, configure, deploy, document, and support solutions. Draft a one-page implementation and support handoff for a hypothetical AI-enabled workflow, covering intended behavior, user steps, and how issues would be reported.
Training and enablement delivery
Developing and delivering training and documentation is a stated responsibility. Create a brief session outline for one of the posting’s user groups, including a demonstration, a practice activity, and a way to collect questions or feedback.
Monitoring and incident troubleshooting
The posting requires platform-performance monitoring and incident troubleshooting. Practice writing a concise incident record for a simulated alert: observed symptoms, impact, diagnostic steps, technical-team coordination, restoration status, and follow-up.

Your preparation checklist

Map evidence to the stated qualifications
Prepare a one-page evidence sheet covering the posted experience thresholds, relevant degree, AI tools you have used, requirements work, technical documentation, training, incident support, and familiarity with DevOps, MLOps, or CI/CD. Note technical certifications only if applicable; the posting says they are preferred.
Rehearse an AI solution walkthrough
Choose a real project, if available, and explain the user need, stakeholder discussions, process map, technical specifications, configuration or deployment, documentation, and outcome. Be precise about your own role and any measured results.
Practice a university workflow design exercise
For a hypothetical staff, faculty, or student workflow, draft discovery questions, a simple process map, an AI-enabled solution outline, and a short demo plan. Label assumptions; the posting does not identify a specific project.
Outline a platform lifecycle plan
Prepare a sample roadmap showing how you would prioritize enhancements, coordinate change management and user support, monitor usage, collect feedback, and decide what to improve. These activities are named in the role.
Create a brief adoption artifact
Draft a one-page user guide or short training outline for a tool you know, such as Copilot or Claude. Include a demonstration task, support guidance, and a way to gather feedback from diverse users.
Walk through an incident response
Prepare a concise example or hypothetical response covering an alert, business-impact triage, troubleshooting, coordination with technical teams, service restoration, and follow-up documentation. The posting specifies rotating availability outside normal hours.
Write targeted questions for the employer
Ask which AI platforms and user groups are the initial priorities, how adoption and platform health are assessed, how ownership is shared across teams, and how the rotating coverage works. The posting also specifies at least three Boston office days per week.

Availability last checked: Nov 4, 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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