Assistant Vice President, AI Engineering
About The Position
Southern New Hampshire University is looking for an AVP of AI Engineering reporting to the Vice President of AI Engineering. As a senior engineering leader, you will oversee operational execution, technical quality, and delivery reliability across the AI Engineering organization. This is the role accountable for ensuring AI projects move from strategy to stable, maintainable production systems - on time and at quality. You will combine people leadership, technical depth, and operational thoughtfulness. The AVP drives daily AI engineering execution, makes and guides technical decisions across the organization, and builds the operational practices and team culture that sustain high-quality delivery. This includes setting the standard for AI-augmented engineering - shaping how we adopt AI development tools and evolving our definition of engineering productivity. You will work remotely from any of our approved states.
Requirements
- 10+ years of software engineering experience, with time in production systems
- 5+ years leading engineering teams through managers or senior technical leads
- Experience overseeing delivery for complex, multi-team technical projects
- Expertise balancing technical depth with people and operational leadership
- Experience in production software systems engineering
- Experience building and operating AI-enabled systems in production environments
- Experience with agentic AI architecture, LLM-based systems, and agent orchestration patterns
- Experience with cloud infrastructure (AWS, Azure, or equivalent), data pipelines, and system reliability
- Experience with evaluation methodologies for LLMs and agentic systems (offline evals, human-in-the-loop, production monitoring)
- Experience with AI development tools (GitHub Copilot, Cursor, Claude Code, or similar)
- Experience with complex architecture reviews, technical tradeoffs, and debugging when needed
- Experience establishing engineering processes that improve predictability without bureaucracy
- Familiarity with on-call models, incident response, and production operations
- Experience improving engineering quality, delivery speed, and system stability
Responsibilities
- Lead operational delivery across AI Engineering: planning, staffing, execution, and shipment of projects
- Translate strategy into executable technical plans, milestones, and resourcing models
- Maintain visibility into project status, risks, dependencies, and delivery health
- Guide execution practices across teams (planning cadences, estimation, delivery reviews, retrospectives, postmortems)
- Ensure production readiness, on-call practices, and incident response processes are in place and improving
- Lead long-term sustainability of AI systems post-launch, including maintenance, monitoring, and ongoing optimization
- Be senior technical authority for AI Engineering and infrastructure decisions
- Guide architecture for agentic AI systems, data platforms, evaluation frameworks, and production services - with a focus on scalability, reliability, security, cost efficiency, and observability
- Establish organizational standards for agent orchestration, memory, and tool use patterns
- Lead cost governance for LLM-based systems (token economics, model selection tradeoffs)
- Define evaluation strategy for LLM and agent-based systems, ensuring measurable performance criteria exist before production deployment
- Partner with Staff and Principal Engineers across SNHU to establish and promote adherence to AI technical standards
- Directly manage engineering and senior technical leads
- Coach managers on delivery, performance, and team development
- Lead staffing, hiring, onboarding and career growth
- Foster a culture of accountability, psychological safety, and continuous improvement
- Partner across SNHU teams, including AI Governance, Product, Data Science, Design, IT, and Academic partners to ensure smooth execution
- Communicate delivery progress, tradeoffs, and constraints to senior leadership
- Help translate technical realities into applicable decisions for senior leadership
- 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
Benefits
- High-quality, low-deductible medical insurance
- Low to no-cost dental and vision plans
- 5 weeks of paid time off (plus almost a dozen paid holidays)
- Employer-funded retirement
- Free tuition program
- Parental leave
- Mental health and wellbeing resources
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What This Job Offers
Job Type
Full-time
Career Level
Executive
Education Level
No Education Listed
