• You will lead operational delivery across AI Engineering: planning, staffing, execution, and shipment of projects • You will translate strategy into executable technical plans, milestones, and resourcing models • You will maintain visibility into project status, risks, dependencies, and delivery health • You will guide execution practices across teams (planning cadences, estimation, delivery reviews, retrospectives, postmortems) • You will ensure production readiness, on-call practices, and incident response processes are in place and improving • You will lead long-term sustainability of AI systems post-launch, including maintenance, monitoring, and ongoing optimization • You will be senior technical authority for AI Engineering and infrastructure decisions • You will guide architecture for agentic AI systems, data platforms, evaluation frameworks, and production services - with a focus on scalability, reliability, security, cost efficiency, and observability • You will establish organizational standards for agent orchestration, memory, and tool use patterns • You will lead cost governance for LLM-based systems (token economics, model selection tradeoffs) • You will define evaluation strategy for LLM and agent-based systems, ensuring measurable performance criteria exist before production deployment • You will partner with Staff and Principal Engineers across SNHU to establish and promote adherence to AI technical standards • You will directly manage engineering and senior technical leads • You will coach managers on delivery, performance, and team development • You will lead staffing, hiring, onboarding and career growth • You will foster a culture of accountability, psychological safety, and continuous improvement • You will partner across SNHU teams, including AI Governance, Product, Data Science, Design, IT, and Academic partners to ensure smooth execution • You will communicate delivery progress, tradeoffs, and constraints to senior leadership • You will help translate technical realities into applicable decisions for senior leadership • You will set expectations and create conditions for AI-augmented development across the organization: tooling decisions, workflow patterns, and evolving standards for how the team uses AI development tools