AI Delivery and Operations Lead,

Description

Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932, our people-centered strategy has defined us — and helped us grow a team that now serves over 180,000 learners worldwide.

Our mission to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And today, we're ready to expand our reach. All we need is you.

Make an impact — from near or far

At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming.

We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states.

The opportunity

The AI Delivery and Operations Lead reports directly to the Assistant Vice President of AI Engineering and leads how SNHU's AI Engineering team plans, coordinates and delivers its work. AI Engineering builds AI software, from LLM applications and agents to the shared platform they run on, in small teams called pods; each pod pairs AI Engineering with the business team that owns the problem. Reporting to the AVP, AI Engineering, the Lead owns the team's operating rhythm, leads delivery of assigned pod initiatives from intake to production, and keeps goals, decisions, risks, and dependencies visible to pods, leadership, and the university IT, security, and AI governance teams that pod work depends on.

This is a player-coach role. The Lead starts as an individual contributor and may build a small delivery team as the number of pods grows; engineers keep their own reporting lines. Success depends on the ability to create clarity from ambiguity, exercise sound judgment, influence without direct authority, and follow work through to outcomes. The role calls for enough AI and software fluency to follow engineering trade-offs and question them, but does not require building AI systems.

You will work 100% remotely in this role. #LI-Remote

What You'll Do:

Operating rhythm: Own the day-to-day operating rhythm of AI Engineering, including weekly syncs, demos, retrospectives, leadership reviews, planning cycles, and decision and action logs, using written and automated updates in place of meetings where possible, so that priorities, decisions, and dependencies stay visible and moving.
Pod stages and go/no-go reviews: Manage the stages every pod moves through, from idea to production and handover to a long-term owner, and the gates between them, such as evaluation results, security and architecture review, and release readiness. Lead regular go/no-go reviews, bring leadership a recommendation to continue, change course, move to production, or stop, and make sure the decision is carried out.
Pod delivery plans: Lead delivery of assigned priority pod initiatives from intake and scoping through build and launch, building integrated plans with clear scope, milestones, accountable owners, dependencies, and success measures across pods, university IT, the AI governance team, and business teams.
OKR tracking: Track AI Engineering's OKRs day to day: follow key-result progress, keep owners accountable, raise risks and blockers early, and supply the key-result data that feeds the university's quarterly planning and reporting.
Intake follow-through: Own AI Engineering's action items from the university's weekly AI intake meeting, track each one to closure, and report status at the next meeting.
Decision support: Turn emerging risks, dependencies, and blockers into concise recommendations and materials for the AVP, AI Engineering, and executive leadership.
Attendance, punctuality, and reliability are essential functions of this role
Other duties and responsibilities as assigned. Job responsibilities can change at any time, with or without notice.

What We're Looking For:

7+ years of progressively responsible experience in program, project, technology delivery, or operations management in a complex, cross-functional environment, including experience delivering technology-enabled initiatives such as enterprise software, data and analytics, automation, or AI.
Bachelor's degree in business, information systems, computer science, or a related field.
Equivalent experience in lieu of degree acceptable.
Working knowledge of how AI applications are built and run, including large language models, retrieval, agents, evaluation, and model and cloud costs, sufficient to follow engineers' trade-offs and question them.
Strong knowledge of software delivery methods, including Agile and hybrid approaches, release planning, risk and dependency management, and goal frameworks such as OKRs.
Experience moving software, data, or AI products from pilot into supported production, including IT, security, and architecture review.
Structured problem solving and the ability to synthesize complex information into clear recommendations.
Clear, concise writing and presentation for audiences up to executive leadership, including plans, decision records, and updates that senior leaders can act on.
Proficiency with work-management tools such as Azure DevOps or Jira.
Ability to create clarity from ambiguity and exercise sound judgment with limited direction.
Ability to influence and hold stakeholders accountable to shared commitments without direct authority.
Ability to manage multiple complex priorities and dependencies at the same time.
Ability to lead and coach delivery staff and set shared practices across several teams.
Ownership mindset, follow-through, and credibility with senior leaders.
Curiosity and commitment to keeping AI knowledge current as the technology evolves.

Preferred Qualifications:

A technical background, such as software or data engineering, technical program management, or engineering management.
Use of AI tools such as Microsoft Copilot or Claude in your own work, including small automations for routine reporting.

We believe real innovation comes from inclusion - where different experiences, perspectives and talents are celebrated. So if you're wondering whether SNHU is right for you, take the leap and apply. You might be just the person we're looking for.

If you have a disability and require a reasonable accommodation to fully engage in any part of the application or hiring process, please complete the Accommodation Request form or contact us at 603-626-9447. A member from the Employee Accommodation Support Center will be in contact with you within two business days to discuss your request.

Compensation

The annual pay range for this position is $88,130.00 - $141,036.00. Actual offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect this position to be hired in the following target hiring range $97,384.00 - $131,756.00.

Exceptional benefits (because you’re exceptional)

You’re the whole package. Your benefits should be, too. As a full-time employee at SNHU, you’ll get: